Merge pull request #87 from CartoDB/release-v1-alpha

Release 0.0.2

.gitignore

@@ -2,3 +2,5 @@
 src/pg/observatory--current--dev.sql
 src/pg/observatory--dev--current.sql
 src/pg/observatory--dev.sql
+venv
+*.pyc

doc/API.md

@@ -1,110 +1,11 @@
-# Data Observatory Access
+# Data Observatory Documentation
 
-This file is for reference purposes only. It is intended for tracking the Data Observatory API functions that should be displayed from the Docs site. Like all API doc, the golden source of the code will live in this repo. I will pull the list of files below into the docs for the output.
+This file is for reference purposes only. It is intended for tracking the Data Observatory functions that should be displayed from the live Docs site. Like all API doc, the golden source of this code will live in this observatory-extension repo, and will be edited in this repo.
 
 ## Documentation
 
-## OBS_GetDemographicSnapshot
-
-The Demographic Snapshot API call enables you to collect demographic details around a point location. For example, you can take the coordinates of a bus stop and find the average population characteristics in that location. If you need help creating coordinates from addresses, [see our geocoding documentation].
-
-Fields returned include information about income, education, transportation, race, and more. Not all fields will have information for every coordinate queried.
-
-
-### API Syntax
-
-```html
-https://{{account name}}.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetDemographicSnapshot({{point geometry}})
-```
-
-#### Parameters
-
-| Parameter  | Description  |  Example  |
-|---|:-:|:-:|
-| account name  | The name of your CartoDB account where the Data Observatory has been enabled  | example_account  |
-| point geometry  |  A WKB point geometry. You can use the helper function, CDB_LatLng to quickly generate one from latitude and longitude | CDB_LatLng(40.760410,-73.964242)  |
-
-#### Geographic Scope
-
-The Demographic Snapshot API is available for the following countries:
-
-* United States
-
-### API Examples
-
-__Get the Demographic Snapshot at Camp David__
-
-```text
-https://example_account.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetDemographicSnapshot(CDB_LatLng(39.648333, -77.465))
-```
-__Get the Demographic Snapshot in the Upper West Side__
-
-```text
-https://example_account.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetDemographicSnapshot(CDB_LatLng(40.80, -73.960))
-```
-
-### API Response
-
-[Click to expand](https://gist.github.com/ohasselblad/c9e59a6e8da35728d0d81dfed131ed17)
-
-### Available fields
-
-The Demographic Snapshot contains a broad subset of demographic measures in the Data Observatory. Over 80 measurements are returned by a single API request.
-
-__todo: turn this spreadsheet into a markdown table__
-
-https://docs.google.com/spreadsheets/d/1U3Uajw_PsIy3_YgeujnJ7AiL2VREdT-ozdaulx07q2g/edit#gid=430723120
-
-## OBS_GetSegmentationSnapshot
-
-The Segmentation Snapshot API call enables you to determine the pre-calculated population segment for a location. For example, you can take the location of a store location and determine what classification of population exists around that location. If you need help creating coordinates from addresses, [see our geocoding documentation].
-
-### API Syntax
-
-```html
-https://{{account name}}.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetSegmentationSnapshot({{point geometry}})
-```
-
-#### Parameters
-
-| Parameter  | Description  |  Example  |
-|---|:-:|:-:|
-| account name  | The name of your CartoDB account where the Data Observatory has been enabled  | example_account  |
-| point geometry  |  A WKB point geometry. You can use the helper function, CDB_LatLng to quickly generate one from latitude and longitude | CDB_LatLng(40.760410,-73.964242)  |
-
-#### Geographic Scope
-
-The Segmentation Snapshot API is available for the following countries:
-
-* United States
-
-### API Examples
-
-__Get the Segmentation Snapshot around the MGM Grand__
-
-```text
-https://example_account.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetSegmentationSnapshot(CDB_LatLng(36.10222, -115.169516))
-```
-__Get the Segmentation Snapshot at CartoDB's NYC HQ__
-
-```text
-https://example_account.cartodb.com/api/v2/sql?q=SELECT * FROM
-OBS_GetSegmentationSnapshot(CDB_LatLng(40.704512, -73.936669))
-```
-
-### API Response
-
-__todo__
-
-### Available segments
-
-__todo__
-
-### Methodology
-
-Segmentation is a method that divides a target market into subgroups based on shared common traits. While we plan to make many different segmentation methods available, our first release includes a segmentation profile first defined in a paper, _Understanding America's Neighborhoods Using Uncertain Data from the American Community Survey: Output Data: US_tract_clusters_new_. [See here](http://www.tandfonline.com/doi/pdf/10.1080/00045608.2015.1052335) for further information on the work in that paper.  
+* [Measures Functions](measures_functions.md)
+* [Boundary Functions](boundary_functions.md)
+* [Discovery Functions](discovery_functions.md)
+* [Glossary](glossary.md)
+* [License](license.md)

doc/boundary_functions.md

@@ -0,0 +1,274 @@
+# Boundary Functions
+
+Use the following functions to retrieve [Boundary](/cartodb-platform/data/overview/#boundary-data) data. Data ranges from small areas (e.g. US Census Block Groups) to large areas (e.g. Countries). You can access boundaries by point location lookup, bounding box lookup, direct ID access and several other methods described below.
+
+You can [access](/cartodb-platform/data/accessing/#accessing-the-data-observatory) boundaries through the CartoDB Editor. The same methods will work if you are using the CartoDB Platform to develop your application. We [encourage you](/cartodb-platform/data/accessing/#best-practices) to use table modifying methods (UPDATE and INSERT) over dynamic methods (SELECT).
+
+## OBS_GetBoundariesByGeometry(polygon geometry, geometry_id text)
+
+The ```OBS_GetBoundariesByGeometry(geometry, geometry_id)``` method returns a set of boundary geometries that intersect a supplied geometry. This can be used to find all boundaries that are within or overlap a bounding box. You have the ability to choose whether to retrieve all boundaries that intersect your supplied bounding box or only those that fall entirely inside of your bounding box.
+
+#### Arguments
+
+Name |Description
+--- | ---
+polygon | a bounding box or other WGS84 geometry
+geometry_id | a string identifier for a boundary geometry
+timespan (optional) | year(s) to request from ('NULL' (default) gives most recent)
+overlap_type (optional) | one of '[intersects](http://postgis.net/docs/manual-2.2/ST_Intersects.html)' (default), '[contains](http://postgis.net/docs/manual-2.2/ST_Contains.html)', or '[within](http://postgis.net/docs/manual-2.2/ST_Within.html)'.
+
+#### Returns
+
+A table with the following columns:
+
+Column Name | Description
+--- | ---
+the_geom | a boundary geometry (e.g., US Census tract boundaries)
+geom_refs | a string identifier for the geometry (e.g., geoids of US Census tracts)
+
+If geometries are not found for the requested `polygon`, `geometry_id`, `timespan`, or `overlap_type`, then null values are returned.
+
+#### Example
+
+Insert all Census Tracts from Lower Manhattan and nearby areas within the supplied bounding box to a table named `manhattan_census_tracts` which has columns `the_geom` (geometry) and `geom_refs` (text).
+
+```sql
+INSERT INTO manhattan_census_tracts(the_geom, geom_refs)
+SELECT *
+FROM OBS_GetBoundariesByGeometry(
+       ST_MakeEnvelope(-74.0251922607,40.6945658517,
+                      -73.9651107788,40.7377626342,
+                      4326),
+       'us.census.tiger.census_tract')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed as the first argument, an error is thrown: `Invalid geometry type (ST_Polygon), expecting 'ST_Point'`
+* If an `overlap_type` other than the valid ones listed above is entered, then an error is thrown
+
+## OBS_GetPointsByGeometry(polygon geometry, geometry_id text)
+
+The ```OBS_GetPointsByGeometry(polygon, geometry_id)``` method returns point geometries and their geographical identifiers that intersect (or are contained by) a bounding box polygon and lie on the surface of a boundary corresponding to the boundary with same geographical identifiers (e.g., a point that is on a census tract with the same geoid). This is a useful alternative to ```OBS_GetBoundariesByGeometry``` listed above because it returns much less data for each location.
+
+#### Arguments
+
+Name |Description
+--- | ---
+polygon | a bounding box or other geometry
+geometry_id | a string identifier for a boundary geometry
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+overlap_type (optional) | one of '[intersects](http://postgis.net/docs/manual-2.2/ST_Intersects.html)' (default), '[contains](http://postgis.net/docs/manual-2.2/ST_Contains.html)', or '[within](http://postgis.net/docs/manual-2.2/ST_Within.html)'.
+
+#### Returns
+
+A table with the following columns:
+
+Column Name | Description
+--- | ---
+the_geom | a point geometry on a boundary (e.g., a point that lies on a US Census tract)
+geom_refs| a string identifier for the geometry (e.g., the geoid of a US Census tract)
+
+If geometries are not found for the requested geometry, `geometry_id`, `timespan`, or `overlap_type`, then NULL values are returned.
+
+#### Example
+
+Insert points that lie on Census Tracts from Lower Manhattan and nearby areas within the supplied bounding box to a table named `manhattan_tract_points` which has columns `the_geom` (geometry) and `geom_refs` (text).
+
+```sql
+INSERT INTO manhattan_tract_points (the_geom, geom_refs)
+SELECT *
+FROM OBS_GetPointsByGeometry(
+       ST_MakeEnvelope(-74.0251922607,40.6945658517,
+                       -73.9651107788,40.7377626342,
+                       4326),
+       'us.census.tiger.census_tract')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed as the first argument, an error is thrown: `Invalid geometry type (ST_Point), expecting 'ST_MultiPolygon' or 'ST_Polygon'`
+
+## OBS_GetBoundary(point_geometry, boundary_id)
+
+The ```OBS_GetBoundary(point_geometry, boundary_id)``` method returns a boundary geometry defined as overlapping the point geometry and from the desired boundary set (e.g. Census Tracts). See the [Boundary ID glossary table below](below). This is a useful method for performing aggregations of points.
+
+#### Arguments
+
+Name | Description
+--- | ---
+point_geometry | a WGS84 polygon geometry (the_geom)
+boundary_id | a boundary identifier from the [Boundary ID glossary table below](below)
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+
+#### Returns
+
+A boundary geometry. If no value is found at the requested `boundary_id` or `timespan`, a null value is returned.
+
+Value | Description
+--- | ---
+geom | WKB geometry
+
+#### Example
+
+Overwrite a point geometry with a boundary geometry that contains it in your table
+
+```SQL
+UPDATE tablename
+SET the_geom = OBS_GetBoundary(the_geom, 'us.census.tiger.block_group')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed, an error is thrown: `Invalid geometry type (ST_Line), expecting 'ST_Point'`
+
+## OBS_GetBoundaryId(point_geometry, boundary_id)
+
+The ```OBS_GetBoundaryId(point_geometry, boundary_id)``` returns a unique geometry_id for the boundary geometry that contains a given point geometry. See the [Boundary ID glossary table below](below). The method can be combined with ```OBS_GetBoundaryById(geometry_id)``` to create a point aggregation workflow.
+
+#### Arguments
+
+Name |Description
+--- | ---
+point_geometry | a WGS84 point geometry (the_geom)
+boundary_id | a boundary identifier from the [Boundary ID glossary table below](below)
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+
+#### Returns
+
+A TEXT boundary geometry id. If no value is found at the requested `boundary_id` or `timespan`, a null value is returned.
+
+Value | Description
+--- | ---
+geometry_id | a string identifier of a geometry in the Boundaries
+
+#### Example
+
+Write the US Census block group geoid that contains the point geometry for every row as a new column in your table.
+
+```SQL
+UPDATE tablename
+SET geometry_id = OBS_GetBoundaryId(the_geom, 'us.census.tiger.block_group')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed, an error is thrown: `Invalid geometry type (ST_Line), expecting 'ST_Point'`
+
+## OBS_GetBoundaryById(geometry_id, boundary_id)
+
+The ```OBS_GetBoundaryById(geometry_id, boundary_id)``` returns the boundary geometry for a unique geometry_id. A geometry_id can be found using the ```OBS_GetBoundaryId(point_geometry, boundary_id)``` method described above.
+
+#### Arguments
+
+Name | Description
+--- | ---
+geometry_id | a string identifier for a Boundary geometry
+boundary_id | a boundary identifier from the [Boundary ID glossary table below](below)
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+
+#### Returns
+
+A boundary geometry. If a geometry is not found for the requested `geometry_id`, `boundary_id`, or `timespan`, then a null value is returned.
+
+Key | Description
+--- | ---
+geom | a WGS84 polygon geometry
+
+#### Example
+
+Use a table of `geometry_id`s (e.g., geoid from the U.S. Census) to select the unique boundaries that they correspond to and insert into a table called, `overlapping_polygons`. This is a useful method for creating new choropleths of aggregate data.
+
+```SQL
+INSERT INTO overlapping_polygons (the_geom, geometry_id, point_count)
+SELECT
+  OBS_GetBoundaryById(geometry_id, 'us.census.tiger.county') As the_geom,
+  geometry_id,
+  count(*)
+FROM tablename
+GROUP BY geometry_id
+```
+
+## OBS_GetBoundariesByPointAndRadius(point geometry, radius numeric, boundary_id text)
+
+The ```OBS_GetBoundariesByPointAndRadius(point, radius, boundary_id)``` method returns boundary geometries and their geographical identifiers that intersect (or are contained by) a circle centered on a point with a radius.
+
+#### Arguments
+
+Name |Description
+--- | ---
+point | a WGS84 point geometry
+radius | a radius (in meters) from the center point
+geometry_id | a string identifier for a boundary geometry
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+overlap_type (optional) | one of '[intersects](http://postgis.net/docs/manual-2.2/ST_Intersects.html)' (default), '[contains](http://postgis.net/docs/manual-2.2/ST_Contains.html)', or '[within](http://postgis.net/docs/manual-2.2/ST_Within.html)'.
+
+#### Returns
+
+A table with the following columns:
+
+Column Name | Description
+--- | ---
+the_geom | a boundary geometry (e.g., a US Census tract)
+geom_refs| a string identifier for the geometry (e.g., the geoid of a US Census tract)
+
+If geometries are not found for the requested point and radius, `geometry_id`, `timespan`, or `overlap_type`, then null values are returned.
+
+#### Example
+
+Insert into table `denver_census_tracts` the census tract boundaries and geom_refs of census tracts which intersect within 10 miles of downtown Denver, Colorado.
+
+```sql
+INSERT INTO denver_census_tracts(the_geom, geom_refs)
+SELECT *
+FROM OBS_GetBoundariesByPointAndRadius(
+  CDB_LatLng(39.7392, -104.9903), -- Denver, Colorado
+  10000 * 1.609, -- 10 miles (10km * conversion to miles)
+  'us.census.tiger.census_tract')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed, an error is thrown. E.g., `Invalid geometry type (ST_Line), expecting 'ST_Point'`
+
+## OBS_GetPointsByPointAndRadius(point geometry, radius numeric, boundary_id text)
+
+The ```OBS_GetPointsByPointAndRadius(point, radius, boundary_id)``` method returns point geometries on boundaries (e.g., a point that lies on a Census tract) and their geographical identifiers that intersect (or are contained by) a circle centered on a point with a radius.
+
+#### Arguments
+
+Name |Description
+--- | ---
+point | a WGS84 point geometry
+radius | radius (in meters)
+geometry_id | a string identifier for a boundary geometry
+timespan (optional) | year(s) to request from (`NULL` (default) gives most recent)
+overlap_type (optional) | one of '[intersects](http://postgis.net/docs/manual-2.2/ST_Intersects.html)' (default), '[contains](http://postgis.net/docs/manual-2.2/ST_Contains.html)', or '[within](http://postgis.net/docs/manual-2.2/ST_Within.html)'.
+
+#### Returns
+
+A table with the following columns:
+
+Column Name | Description
+--- | ---
+the_geom | a point geometry (e.g., a point on a US Census tract)
+geom_refs | a string identifier for the geometry (e.g., the geoid of a US Census tract)
+
+If geometries are not found for the requested point and radius, `geometry_id`, `timespan`, or `overlap_type`, then null values are returned.
+
+#### Example
+
+Insert into table `denver_tract_points` points on US census tracts and their corresponding geoids for census tracts which intersect within 10 miles of downtown Denver, Colorado, USA.
+
+```sql
+INSERT INTO denver_tract_points(the_geom, geom_refs)
+SELECT *
+FROM OBS_GetPointsByPointAndRadius(
+  CDB_LatLng(39.7392, -104.9903), -- Denver, Colorado
+  10000 * 1.609, -- 10 miles (10km * conversion to miles)
+  'us.census.tiger.census_tract')
+```
+
+#### Errors
+
+* If a geometry other than a point is passed, an error is thrown. E.g., `Invalid geometry type (ST_Line), expecting 'ST_Point'`

doc/discovery_functions.md

@@ -0,0 +1,58 @@
+# Discovery Functions
+
+If you are using the [discovery methods](/cartodb-platform/data/overview/#discovery-methods) from the Data Observatory, use the following functions to retrieve [boundary](/cartodb-platform/data/overview/#boundary-data) and [measures](/cartodb-platform/data/overview/#measures-data) data.
+
+## OBS_Search(search_term)
+
+Use arbitrary text to search all available measures
+
+#### Arguments
+
+Name | Description
+--- | ---
+search_term | a string to search for available measures
+boundary_id | a string identifier for a boundary geometry (optional)
+
+#### Returns
+
+A TABLE containing the following properties
+
+Key | Description
+--- | ---
+id | the unique id of the measure for use with the ```OBS_GetMeasure``` function
+name | the human readable name of the measure
+description | a brief description of the measure
+aggregate | **sum** are raw count values, **median** are statistical medians, **average** are statistical averages, **undefined** other (e.g. an index value)
+source | where the data came from (e.g. US Census Bureau)
+
+#### Example
+
+```SQL
+SELECT * FROM OBS_Search('home value')
+```
+
+## OBS_GetAvailableBoundaries(point_geometry)
+
+Returns available `boundary_id`s at a given point geometry.
+
+#### Arguments
+
+Name | Description
+--- | ---
+point_geometry |  a WGS84 point geometry (e.g. the_geom)
+
+#### Returns
+
+A TABLE containing the following properties
+
+Key | Description
+--- | ---
+boundary_id | a boundary identifier from the [boundary ID glossary](/cartodb-platform/data/glossary/#boundary-ids)
+description | a brief description of the boundary dataset
+time_span | the timespan attached the boundary. this does not mean that the boundary is invalid outside of the timespan, but is the explicit timespan published with the geometry.
+
+#### Example
+
+```SQL
+SELECT * FROM OBS_GetAvailableBoundaries(CDB_LatLng(40.7, -73.9))
+```

doc/glossary.md

@@ -0,0 +1,126 @@
+# Glossary
+
+A list of boundary ids and measure_names for Data Observatory functions. For US based boundaries, the Shoreline Clipped version provides a high-quality shoreline clipping for mapping uses.
+
+## Boundary IDs
+
+Boundary name | Boundary ID | Shoreline Clipped Boundary ID
+--------------------- | --------------------- | ---
+US States  |  us.census.tiger.state  |  us.census.tiger.state_clipped
+US County  |  us.census.tiger.county  |  us.census.tiger.county_clipped
+US Census Zip Code Tabulation Areas  |  us.census.tiger.zcta5  |  us.census.tiger.zcta5_clipped
+US Census Tracts  |  us.census.tiger.census_tract  |  us.census.tiger.census_tract_clipped
+US Elementary School District  |  us.census.tiger.school_district_elementary  |  us.census.tiger.school_district_elementary_clipped
+US Secondary School District  |  us.census.tiger.school_district_secondary  |  us.census.tiger.school_district_secondary_clipped
+US Unified School District  |  us.census.tiger.school_district_unified  |  us.census.tiger.school_district_unified_clipped
+US Congressional Districts  |  us.census.tiger.congressional_district  |  us.census.tiger.congressional_district_clipped
+US Census Blocks  |  us.census.tiger.block  |  us.census.tiger.block_clipped
+US Census Block Groups  |  us.census.tiger.block_group  |  us.census.tiger.block_group_clipped
+US Census PUMAs  |  us.census.tiger.puma  |  us.census.tiger.puma_clipped
+US Incorporated Places  |  us.census.tiger.place  |  us.census.tiger.place_clipped
+ES Sección Censal  |  es.ine.geom  |   none
+Regions (First-level Administrative)  |  whosonfirst.wof_region_geom  |   none
+Continents  |  whosonfirst.wof_continent_geom  |   none
+Countries  |  whosonfirst.wof_country_geom  |  none
+Marine Areas  |  whosonfirst.wof_marinearea_geom  |  none
+Disputed Areas  |  whosonfirst.wof_disputed_geom  |  none
+
+
+
+## OBS_GetUSCensusMeasure Names Table
+
+This list contains human readable names accepted in the ```OBS_GetUSCensusMeasure``` function. For the more comprehensive list of columns available to the ```OBS_GetMeasure``` function, see the [Data Observatory Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf).
+
+Measure name             |  Measure description
+------------------------ | --------------------
+Male Population   |   The number of people within each geography who are male.
+Female Population   |   The number of people within each geography who are female.
+Median Age   |   The median age of all people in a given geographic area.
+Total Population   |   The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.
+Population not Hispanic   |   The number of people not identifying as Hispanic or Latino in each geography.
+White Population   |   The number of people identifying as white, non-Hispanic in each geography.
+Black or African American Population   |   The number of people identifying as black or African American, non-Hispanic in each geography.
+American Indian and Alaska Native Population   |   The number of people identifying as American Indian or Alaska native in each geography.
+Asian Population   |   The number of people identifying as Asian, non-Hispanic in each geography.
+Other Race population   |   The number of people identifying as another race in each geography.
+Two or more races population   |   The number of people identifying as two or more races in each geography.
+Hispanic Population   |   The number of people identifying as Hispanic or Latino in each geography.
+Not a U.S. Citizen Population   |   The number of people within each geography who indicated that they are not U.S. citizens.
+Workers over the Age of 16   |   The number of people in each geography who work. Workers include those employed at private for-profit companies, the self-employed, government workers and non-profit employees.
+Commuters by Car, Truck, or Van   |   The number of workers age 16 years and over within  a geographic area who primarily traveled to work by car, truck or  van.  This is the principal mode of travel or type of conveyance,  by distance rather than time, that the worker usually used to get  from home to work.
+Commuters who drove alone   |   The number of workers age 16 years and over within a geographic area who primarily traveled by car driving alone. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.
+Commuters by Carpool   |   The number of workers age 16 years and over within a geographic area who primarily traveled to work by carpool.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.
+Commuters by Bus   |   The number of workers age 16 years and over within a geographic area who primarily traveled to work by bus.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.
+Commuters by Subway or Elevated   |   The number of workers age 16 years and over within a geographic area who primarily traveled to work by subway or elevated train.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.
+Walked to Work   |   The number of workers age 16 years and over within a geographic area who primarily walked to work.  This would mean that of any way of getting to work, they travelled the most distance walking.
+Worked at Home   |   The count within a geographical area of workers over the age of 16 who worked at home.
+Workers age 16 and over who do not work from home   |   The number of workers over the age of 16 who do not work from home in a geographic area.
+Number of workers with less than 10 minute commute   |   The number of workers over the age of 16 who do not work from home and commute in less than 10 minutes in a geographic area.
+Number of workers with a commute between 35 and 44 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 35 and 44 minutes in a geographic area.
+Number of workers with a commute of over 60 minutes   |   The number of workers over the age of 16 who do not work from home and commute in over 60 minutes in a geographic area.
+Aggregate travel time to work   |   The total number of minutes every worker over the age of 16 who did not work from home spent spent commuting to work in one day in a geographic area.
+Commuters by Public Transportation   |   The number of workers age 16 years and over within a geographic area who primarily traveled to work by public transportation.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.
+Number of workers with a commute between 10 and 14 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 10 and 14 minutes in a geographic area.
+Number of workers with a commute between 15 and 19 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 15 and 19 minutes in a geographic area.
+Number of workers with a commute between 20 and 24 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 20 and 24 minutes in a geographic area.
+Number of workers with a commute between 25 and 29 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 25 and 29 minutes in a geographic area.
+Number of workers with a commute between 30 and 34 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 30 and 34 minutes in a geographic area.
+Number of workers with a commute between 45 and 59 minutes   |   The number of workers over the age of 16 who do not work from home and commute in between 45 and 59 minutes in a geographic area.
+Children under 18 Years of Age   |   The number of people within each geography who are under 18 years of age.
+Households   |   A count of the number of households in each geography. A household consists of one or more people who live in the same dwelling and also share at meals or living accommodation, and may consist of a single family or some other grouping of people.
+Population 15 Years and Over   |   The number of people in a geographic area who are over the age of 15.  This is used mostly as a denominator of marital status.
+Never Married   |   The number of people in a geographic area who have never been married.
+Currently married   |   The number of people in a geographic area who are currently married.
+Married but separated   |   The number of people in a geographic area who are married but separated.
+Widowed   |   The number of people in a geographic area who are widowed.
+Divorced   |   The number of people in a geographic area who are divorced.
+Population 3 Years and Over   |   The total number of people in each geography age 3 years and over.  This denominator is mostly used to calculate rates of school enrollment.
+Students Enrolled in School   |   The total number of people in each geography currently enrolled at any level of school, from nursery or pre-school to advanced post-graduate education.  Only includes those over the age of 3.
+Students Enrolled in Grades 1 to 4   |   The total number of people in each geography currently enrolled in grades 1 through 4 inclusive.  This corresponds roughly to elementary school.
+Students Enrolled in Grades 5 to 8   |   The total number of people in each geography currently enrolled in grades 5 through 8 inclusive.  This corresponds roughly to middle school.
+Students Enrolled in Grades 9 to 12   |   The total number of people in each geography currently enrolled in grades 9 through 12 inclusive.  This corresponds roughly to high school.
+Students Enrolled as Undergraduate in College   |   The number of people in a geographic area who are enrolled in college at the undergraduate level. Enrollment refers to being registered or listed as a student in an educational program leading to a college degree. This may be a public school or college, a private school or college.
+Population 25 Years and Over   |   The number of people in a geographic area who are over the age of 25.  This is used mostly as a denominator of educational attainment.
+Population Completed High School   |   The number of people in a geographic area over the age of 25 who completed high school, and did not complete a more advanced degree.
+Population completed less than one year of college, no degree   |   The number of people in a geographic area over the age of 25 who attended college for less than one year and no further.
+Population completed more than one year of college, no degree   |   The number of people in a geographic area over the age of 25 who attended college for more than one year but did not obtain a degree.
+Population Completed Associate's Degree   |   The number of people in a geographic area over the age of 25 who obtained a associate's degree, and did not complete a more advanced degree.
+Population Completed Bachelor's Degree   |   The number of people in a geographic area over the age of 25 who obtained a bachelor's degree, and did not complete a more advanced degree.
+Population Completed Master's Degree   |   The number of people in a geographic area over the age of 25 who obtained a master's degree, but did not complete a more advanced degree.
+Population 5 Years and Over   |   The number of people in a geographic area who are over the age of 5.  This is primarily used as a denominator of measures of language spoken at home.
+Speaks only English at Home   |   The number of people in a geographic area over age 5 who speak only English at home.
+Speaks Spanish at Home   |   The number of people in a geographic area over age 5 who speak Spanish at home, possibly in addition to other languages.
+Population for Whom Poverty Status Determined   |   The number of people in each geography who could be identified as either living in poverty or not.  This should be used as the denominator when calculating poverty rates, as it excludes people for whom it was not possible to determine poverty.
+Income In The Past 12 Months Below Poverty Level   |   The number of people in a geographic area who are part of a family (which could be just them as an individual) determined to be in poverty following the Office of Management and Budget's Directive 14. (https://www.census.gov/hhes/povmeas/methodology/ombdir14.html)
+Households with income less than $10,000   |   The number of households in a geographic area whose annual income was less than $10,000.
+Households with income of $10,000 to $14,999   |   The number of households in a geographic area whose annual income was between $10,000 and $14,999.
+Households with income of $15,000 to $19,999   |   The number of households in a geographic area whose annual income was between $15,000 and $19,999.
+Households with income of $20,000 To $24,999   |   The number of households in a geographic area whose annual income was between $20,000 and $24,999.
+Households with income of $25,000 To $29,999   |   The number of households in a geographic area whose annual income was between $20,000 and $24,999.
+Households with income of $30,000 To $34,999   |   The number of households in a geographic area whose annual income was between $30,000 and $34,999.
+Households with income of $35,000 To $39,999   |   The number of households in a geographic area whose annual income was between $35,000 and $39,999.
+Households with income of $40,000 To $44,999   |   The number of households in a geographic area whose annual income was between $40,000 and $44,999.
+Households with income of $45,000 To $49,999   |   The number of households in a geographic area whose annual income was between $45,000 and $49,999.
+Households with income of $50,000 To $59,999   |   The number of households in a geographic area whose annual income was between $50,000 and $59,999.
+Households with income of $60,000 To $74,999   |   The number of households in a geographic area whose annual income was between $60,000 and $74,999.
+Households with income of $75,000 To $99,999   |   The number of households in a geographic area whose annual income was between $75,000 and $99,999.
+Households with income of $100,000 To $124,999   |   The number of households in a geographic area whose annual income was between $100,000 and $124,999.
+Households with income of $125,000 To $149,999   |   The number of households in a geographic area whose annual income was between $125,000 and $149,999.
+Households with income of $150,000 To $199,999   |   The number of households in a geographic area whose annual income was between $150,000 and $1999,999.
+Households with income of $200,000 Or More   |   The number of households in a geographic area whose annual income was more than $200,000.
+Median Household Income in the past 12 Months   |   Within a geographic area, the median income received by every household on a regular basis before payments for personal income taxes, social security, union dues, medicare deductions, etc.  It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans' (VA) payments, unemployment and/or worker's compensation, child support, and alimony.
+Population age 16 and over   |   The number of people in each geography who are age 16 or over.
+Population in Labor Force   |   The number of people in each geography who are either in the civilian labor force or are members of the U.S. Armed Forces (people on active duty with the United States Army, Air Force, Navy, Marine Corps, or Coast Guard).
+Population in Civilian Labor Force   |   The number of civilians 16 years and over in each geography who can be classified as either employed or unemployed below.
+Employed Population   |   The number of civilians 16 years old and over in each geography who either (1) were at work, that is, those who did any work at all during the reference week as paid employees, worked in their own business or profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm or in a family business; or (2) were with a job but not at work, that is, those who did not work during the reference week but had jobs or businesses from which they were temporarily absent due to illness, bad weather, industrial dispute, vacation, or other personal reasons. Excluded from the employed are people whose only activity consisted of work around the house or unpaid volunteer work for religious, charitable, and similar organizations; also excluded are all institutionalized people and people on active duty in the United States Armed Forces.
+Unemployed Population   |   The number of civilians in each geography who are 16 years old and over and are classified as unemployed.
+Population in Armed Forces   |   The number of people in each geography who are members of the U.S. Armed Forces (people on active duty with the United States Army, Air Force, Navy, Marine Corps, or Coast Guard).
+Population Not in Labor Force   |   The number of people in each geography who are 16 years old and over who are not classified as members of the labor force. This category consists mainly of students, homemakers, retired workers, seasonal workers interviewed in an off season who were not looking for work, institutionalized people, and people doing only incidental unpaid family work.
+Housing Units   |   A count of housing units in each geography.  A housing unit is a house, an apartment, a mobile home or trailer, a group of rooms, or a single room occupied as separate living quarters, or if vacant, intended for occupancy as separate living quarters.
+Vacant Housing Units   |   The count of vacant housing units in a geographic area. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.
+Vacant Housing Units for Rent   |   The count of vacant housing units in a geographic area that are for rent. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.
+Vacant Housing Units for Sale   |   The count of vacant housing units in a geographic area that are for sale. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.
+Median Rent   |   The median contract rent within a geographic area. The contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.
+Percent of Household Income Spent on Rent   |   Within a geographic area, the median percentage of household income which was spent on gross rent.  Gross rent is the amount of the contract rent plus the estimated average monthly cost of utilities (electricity, gas, water, sewer etc.) and fuels (oil, coal, wood, etc.) if these are paid by the renter.  Household income is the sum of the income of all people 15 years and older living in the household.
+Owner-occupied Housing Units valued at $1,000,000 or more.   |   The count of owner occupied housing units in a geographic area that are valued at $1,000,000 or more.  Value is the respondent's estimate of how much the property (house and lot, mobile home and lot, or condominium unit) would sell for if it were for sale.
+Owner-occupied Housing Units with a Mortgage   |   The count of housing units within a geographic area that are mortagaged. Mortgage refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust, trust deed, contracts to purchase, land contracts, junior mortgages, and home equity loans.

doc/license.md

@@ -0,0 +1,18 @@
+# License
+
+The Data Observatory is a collection of various sources of data with varying licenses. We have worked hard to find you data that will work for the broadest set of use-cases. For competency, please still review the terms for any dataset you use and respect the rights of the owners for each dataset. The following third-party data sources are used in the Data Observatory, and we have included the links to the terms governing their use.
+
+Name  | Terms link 
+-------|---------
+ACS   |  [https://www.usa.gov/government-works](https://www.usa.gov/government-works)
+TIGER   |  [https://www.usa.gov/government-works](https://www.usa.gov/government-works)
+Zillow Home Value Index | This data is "Aggregate Data", per the Zillow Terms of Use<br /><br />[http://www.zillow.com/corp/Terms.htm](http://www.zillow.com/corp/Terms.htm)
+Who's on First |  [http://whosonfirst.mapzen.com#License](http://whosonfirst.mapzen.com#License)
+GeoNames  |  [http://www.geonames.org/](http://www.geonames.org/)
+GeoPlanet  |  [https://developer.yahoo.com/geo/geoplanet/](https://developer.yahoo.com/geo/geoplanet/)
+Natural Earth  |  [http://www.naturalearthdata.com/about/terms-of-use/](http://www.naturalearthdata.com/about/terms-of-use/)
+Quattroshapes  |  [https://github.com/foursquare/quattroshapes/blob/master/LICENSE.md](https://github.com/foursquare/quattroshapes/blob/master/LICENSE.md)
+Zetashapes  |  [http://zetashapes.com/license](http://zetashapes.com/license)
+Spielman & Singleton  |  [https://www.openicpsr.org/repoEntity/show/41329](https://www.openicpsr.org/repoEntity/show/41329)
+Instituto Nacional de Estadistica  |  [http://www.ine.es/ss/Satellite?L=0&c=Page&cid=1254735849170&p=1254735849170&pagename=Ayuda%2FINELayout](http://www.ine.es/ss/Satellite?L=0&c=Page&cid=1254735849170&p=1254735849170&pagename=Ayuda%2FINELayout)
+

doc/measures_functions.md

@@ -0,0 +1,163 @@
+# Measures Functions
+
+[Data Observatory Measures](/cartodb-platform/data/overview/#measures-methods) are the numerical location data you can access. The measure functions allow you to access individual measures to augment your own data or integrate in your analysis workflows. Measures are used by sending an identifier or a geometry (point or polygon) and receiving back a measure (an absolute value) for that location.
+
+There are hundreds of measures and the list is growing with each release. You can currently discover and learn about measures contained in the Data Observatory by downloading our [Data Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf).
+
+You can [access](/cartodb-platform/data/accessing/#accessing-the-data-observatory) measures through the CartoDB Editor. The same methods will work if you are using the CartoDB Platform to develop your application. We [encourage you](/cartodb-platform/data/accessing/#best-practices) to use table modifying methods (UPDATE and INSERT) over dynamic methods (SELECT).
+
+## OBS_GetUSCensusMeasure(point geometry, measure_name text)
+
+The ```OBS_GetUSCensusMeasure(point, measure_name)``` function returns a measure based on a subset of the US Census variables at a point location. The ```OBS_GetUSCensusMeasure``` function is limited to only a subset of all measures that are available in the Data Observatory, to access the full list, use measure IDs with the ```OBS_GetMeasure``` function below.
+
+#### Arguments
+
+Name |Description
+--- | ---
+point | a WGS84 point geometry (the_geom)
+measure_name | a human readable name of a US Census variable. The list of measure_names is [available in the glossary](/cartodb-platform/data/glossary/#obsgetuscensusmeasure-names-table).
+normalize | for measures that are are **sums** (e.g. population) the default normalization is 'area' and response comes back as a rate per square kilometer. Other options are 'denominator', which will use the denominator specified in the [Data Catalog](http://cartodb.github.io/bigmetadata/index.html) (optional)
+boundary_id | source of geometries to pull measure from (e.g., 'us.census.tiger.census_tract')
+time_span | time span of interest (e.g., 2010 - 2014)
+
+#### Returns
+
+A NUMERIC value
+
+Key | Description
+--- | ---
+value | the raw or normalized measure
+
+#### Example
+
+Add a measure to an empty numeric column based on point locations in your table.
+
+```SQL
+UPDATE tablename
+SET total_population = OBS_GetUSCensusMeasure(the_geom, 'Total Population')
+```
+
+## OBS_GetUSCensusMeasure(polygon geometry, measure_name text)
+
+The ```OBS_GetUSCensusMeasure(point, measure_name)``` function returns a measure based on a subset of the US Census variables within a given polygon. The ```OBS_GetUSCensusMeasure``` function is limited to only a subset of all measures that are available in the Data Observatory, to access the full list, use the ```OBS_GetUSCensusMeasure``` function below.
+
+#### Arguments
+
+Name |Description
+--- | ---
+polygon | a WGS84 polygon geometry (the_geom)
+measure_name | a human readable string name of a US Census variable. The list of measure_names is [available in the glossary](/cartodb-platform/data/glossary/#obsgetuscensusmeasure-names-table).
+normalize | for measures that are **sums** (e.g. population) the default normalization is 'none' and response comes back as a raw value. Other options are 'denominator', which will use the denominator specified in the [Data Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf) (optional)
+boundary_id | source of geometries to pull measure from (e.g., 'us.census.tiger.census_tract')
+time_span | time span of interest (e.g., 2010 - 2014)
+
+#### Returns
+
+A NUMERIC value
+
+Key | Description
+--- | ---
+value | the raw or normalized measure
+
+#### Example
+
+Add a measure to an empty numeric column based on polygons in your table
+
+```SQL
+UPDATE tablename
+SET local_male_population = OBS_GetUSCensusMeasure(the_geom, 'Male Population')
+```
+
+## OBS_GetMeasure(point geometry, measure_id text)
+
+The ```OBS_GetMeasure(point, measure_id)``` function returns any Data Observatory measure at a point location. You can browse all available Measures in the [Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf)).
+
+#### Arguments
+
+Name |Description
+--- | ---
+point | a WGS84 point geometry (the_geom)
+measure_id | a measure identifier from the Data Observatory ([see available measures](https://cartodb.github.io/bigmetadata/observatory.pdf)). It is important to note that these are different than 'measure_name' used in the Census based functions above.
+normalize | for measures that are are **sums** (e.g. population) the default normalization is 'area' and response comes back as a rate per square kilometer. The other option is 'denominator', which will use the denominator specified in the [Data Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf). (optional)
+boundary_id | source of geometries to pull measure from (e.g., 'us.census.tiger.census_tract')
+time_span | time span of interest (e.g., 2010 - 2014)
+
+#### Returns
+
+A NUMERIC value
+
+Key | Description
+--- | ---
+value | the raw or normalized measure
+
+#### Example
+
+Add a measure to an empty numeric column based on point locations in your table
+
+```SQL
+UPDATE tablename
+SET median_home_value_sqft = OBS_GetMeasure(the_geom, 'us.zillow.AllHomes_MedianValuePerSqft')
+```
+
+## OBS_GetMeasure(polygon geometry, measure_id text)
+
+The ```OBS_GetMeasure(polygon, measure_id)``` function returns any Data Observatory measure calculated within a polygon.
+
+#### Arguments
+
+Name |Description
+--- | ---
+polygon_geometry | a WGS84 polygon geometry (the_geom)
+measure_id | a measure identifier from the Data Observatory ([see available measures](https://cartodb.github.io/bigmetadata/observatory.pdf))  
+normalize | for measures that are are **sums** (e.g. population) the default normalization is 'none' and response comes back as a raw value. Other options are 'denominator', which will use the denominator specified in the [Data Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf) (optional)
+boundary_id | source of geometries to pull measure from (e.g., 'us.census.tiger.census_tract')
+time_span | time span of interest (e.g., 2010 - 2014)
+
+#### Returns
+
+A NUMERIC value
+
+Key | Description
+--- | ---
+value | the raw or normalized measure
+
+#### Example
+
+Add a measure to an empty column based on polygons in your table
+
+```SQL
+UPDATE tablename
+SET household_count = OBS_GetMeasure(the_geom, 'us.census.acs.B11001001')
+```
+
+#### Errors
+
+* If an unrecognized normalization type is input, raise an error: `'Only valid inputs for "normalize" are "area" (default) and "denominator".`
+
+## OBS_GetCategory(point geometry, category_id text)
+
+The ```OBS_GetCategory(point, category_id)``` function returns any Data Observatory Category value at a point location. The Categories available are currently limited to Segmentation categories. See the Segmentation section of the [Catalog](https://cartodb.github.io/bigmetadata/observatory.pdf) for more detail.
+
+#### Arguments
+
+Name |Description
+--- | ---
+point | a WGS84 point geometry (the_geom)
+category_id | a category identifier from the Data Observatory ([see available measures](https://cartodb.github.io/bigmetadata/observatory.pdf)).
+
+#### Returns
+
+A TEXT value
+
+Key | Description
+--- | ---
+value | a text based category found at the supplied point
+
+#### Example
+
+Add the Category to an empty column text column based on point locations in your table
+
+```SQL
+UPDATE tablename
+SET segmentation = OBS_GetCategory(the_geom, 'us.census.spielman_singleton_segments.X55')
+```

release/observatory.control

@@ -1,5 +1,5 @@
 comment = 'CartoDB Observatory backend extension'
-default_version = '0.0.1'
+default_version = '0.0.2'
 requires = 'postgis'
 superuser = true
 schema = cdb_observatory

scripts/README.md

@@ -0,0 +1,19 @@
+## Automatic tests and utilities
+
+### Installation
+
+Python 2.7 should cover you.  Virtualenv recommended.
+
+    virtualenv venv
+    source venv/bin/activate
+    pip install -r requirements.txt
+
+### Execution
+
+Currently, we don't have direct access to the metadata end-to-end.  This only
+affects the generation of tests.  As a stopgap, we have to define a connection
+to the test Observatory account.
+
+Run automated tests against a hostname:
+
+    (venv) OBS_HOSTNAME=<hostname.cartodb.com> OBS_API_KEY=<api_key> OBS_META_HOSTNAME=observatory.cartodb.com OBS_META_API_KEY= nosetests scripts/autotest.py

scripts/autotest.py

@@ -0,0 +1,100 @@
+from nose.tools import assert_equal, assert_is_not_none
+from nose_parameterized import parameterized
+
+import os
+import re
+import requests
+
+HOSTNAME = os.environ['OBS_HOSTNAME']
+API_KEY = os.environ['OBS_API_KEY']
+META_HOSTNAME = os.environ.get('OBS_META_HOSTNAME', HOSTNAME)
+META_API_KEY = os.environ.get('OBS_META_API_KEY', API_KEY)
+USE_SCHEMA = 'OBS_USE_SCHEMA' in os.environ
+
+
+def query(q, is_meta=False, **options):
+    '''
+    Query the account.  Returned is the response, wrapped by the requests
+    library.
+    '''
+    url = 'https://{hostname}/api/v2/sql'.format(
+        hostname=META_HOSTNAME if is_meta else HOSTNAME)
+    params = options.copy()
+    params['q'] = re.sub(r'\s+', ' ', q)
+    params['api_key'] = META_API_KEY if is_meta else API_KEY
+    return requests.get(url, params=params)
+
+MEASURE_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM obs_column
+WHERE type ILIKE 'numeric'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+CATEGORY_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM obs_column
+WHERE type ILIKE 'text'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+BOUNDARY_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM obs_column
+WHERE type ILIKE 'geometry'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+def default_point(column_id):
+    '''
+    Returns default test point for the column_id.
+    '''
+    if column_id == 'whosonfirst.wof_disputed_geom':
+        return 'CDB_LatLng(33.78, 76.57)'
+    elif column_id == 'whosonfirst.wof_marinearea_geom':
+        return 'CDB_LatLng(43.33, -68.47)'
+    elif column_id in ('us.census.tiger.school_district_elementary',
+                       'us.census.tiger.school_district_secondary',
+                       'us.census.tiger.school_district_elementary_clipped',
+                       'us.census.tiger.school_district_secondary_clipped'):
+        return 'CDB_LatLng(40.7025, -73.7067)'
+    elif column_id.startswith('es.ine'):
+        return 'CDB_LatLng(40.39, -3.7)'
+    elif column_id.startswith('us.zillow'):
+        return 'CDB_LatLng(28.3305906291771, -81.3544048197256)'
+    else:
+        return 'CDB_LatLng(40.7, -73.9)'
+
+
+@parameterized(MEASURE_COLUMNS)
+def test_measure_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetMeasure({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])
+
+@parameterized(CATEGORY_COLUMNS)
+def test_category_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetCategory({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])
+
+@parameterized(BOUNDARY_COLUMNS)
+def test_boundary_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetBoundary({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])

scripts/generate_fixtures.py

@@ -0,0 +1,85 @@
+
+from sqldumpr import Dumpr
+
+def get_tablename_query(column_id, boundary_id, timespan):
+    """
+        given a column_id, boundary-id (us.census.tiger.block_group), and
+        timespan, give back the current table hash from the data observatory
+    """
+    q = """
+        SELECT t.tablename, geoid_ct.colname colname
+        FROM obs_table t,
+             obs_column_table geoid_ct,
+             obs_column_table data_ct
+        WHERE
+             t.id = geoid_ct.table_id AND
+             t.id = data_ct.table_id AND
+             geoid_ct.column_id =
+        (SELECT source_id
+         FROM obs_column_to_column
+         WHERE target_id = '{boundary_id}'
+         AND reltype = 'geom_ref'
+        ) AND
+        data_ct.column_id = '{column_id}' AND
+        timespan = '{timespan}'
+    """.replace('\n','')
+
+    return q.format(column_id=column_id,
+                    boundary_id=boundary_id,
+                    timespan=timespan)
+
+def select_star(tablename):
+    return "SELECT * FROM {}".format(tablename)
+
+cdb = Dumpr('observatory.cartodb.com','')
+
+metadata = ['obs_table', 'obs_column_table', 'obs_column', 'obs_column_tag', 'obs_tag', 'obs_column_to_column']
+
+fixtures = [
+    ('us.census.tiger.census_tract', 'us.census.tiger.census_tract', '2014'),
+    ('us.census.tiger.block_group', 'us.census.tiger.block_group', '2014'),
+    ('us.census.tiger.zcta5', 'us.census.tiger.zcta5', '2014'),
+    ('us.census.tiger.county', 'us.census.tiger.county', '2014'),
+    ('us.census.acs.B01003001', 'us.census.tiger.census_tract', '2010 - 2014'),
+    ('us.census.acs.B01003001_quantile', 'us.census.tiger.census_tract', '2010 - 2014'),
+    ('us.census.acs.B01003001', 'us.census.tiger.block_group', '2010 - 2014'),
+    ('us.census.spielman_singleton_segments.X10', 'us.census.tiger.census_tract', '2010 - 2014'),
+    ('us.zillow.AllHomes_Zhvi', 'us.census.tiger.zcta5', '2014-01'),
+    ('us.zillow.AllHomes_Zhvi', 'us.census.tiger.zcta5', '2016-03'),
+    ('us.census.tiger.zcta5_clipped', 'us.census.tiger.zcta5_clipped', '2014'),
+    ('us.census.tiger.block_group_clipped', 'us.census.tiger.block_group_clipped', '2014'),
+]
+
+unique_tables = set()
+
+for f in fixtures:
+    column_id, boundary_id, timespan = f
+    tablename_query = get_tablename_query(*f)
+    resp = cdb.query(tablename_query).json()['rows'][0]
+    tablename = resp['tablename']
+    colname = resp['colname']
+    table_colname = (tablename, colname, boundary_id, )
+    if table_colname not in unique_tables:
+        print table_colname
+        unique_tables.add(table_colname)
+
+print unique_tables
+
+with open('src/pg/test/fixtures/load_fixtures.sql', 'w') as outfile:
+    with open('src/pg/test/fixtures/drop_fixtures.sql', 'w') as dropfiles:
+        outfile.write('SET client_min_messages TO WARNING;\n\set ECHO none\n')
+        dropfiles.write('SET client_min_messages TO WARNING;\n\set ECHO none\n')
+        for tablename in metadata:
+            cdb.dump(select_star(tablename), tablename, outfile, schema='observatory')
+            dropfiles.write('DROP TABLE IF EXISTS observatory.{};\n'.format(tablename))
+            print tablename
+
+        for tablename, colname, boundary_id in unique_tables:
+            if 'zcta5' in boundary_id:
+                where = '11%'
+            else:
+                where = '36047%'
+            print ' '.join([select_star(tablename), "WHERE {} LIKE '{}'".format(colname, where)])
+            cdb.dump(' '.join([select_star(tablename), "WHERE {} LIKE '{}'".format(colname, where)]),
+                    tablename, outfile, schema='observatory')
+            dropfiles.write('DROP TABLE IF EXISTS observatory.{};\n'.format(tablename))

scripts/requirements.txt

@@ -0,0 +1,3 @@
+requests
+nose
+nose_parameterized

src/pg/observatory.control

@@ -1,5 +1,5 @@
 comment = 'CartoDB Observatory backend extension'
-default_version = '0.0.1'
+default_version = '0.0.2'
 requires = 'postgis'
 superuser = true
 schema = cdb_observatory

src/pg/sql/40_observatory_utility.sql

@@ -4,8 +4,9 @@
 -- table where there is multiple sources for a column from multiple
 -- geometries.
 CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GeomTable(
-  geom geometry,
-  geometry_id text
+  geom geometry(Geometry, 4326),
+  geometry_id text,
+  time_span text DEFAULT NULL
 )
   RETURNS TEXT
 AS $$
@@ -23,9 +24,11 @@ BEGIN
         AND coltable.column_id = col.id
         AND coltable.table_id = tab.id
         AND col.id = $1
+        AND CASE WHEN $3::TEXT IS NOT NULL THEN timespan ILIKE $3::TEXT ELSE TRUE END
+      ORDER BY timespan DESC LIMIT 1
     )
     '
-  USING geometry_id, geom
+  USING geometry_id, geom, time_span
   INTO result;
 
   return result;
@@ -33,8 +36,6 @@ BEGIN
 END;
 $$ LANGUAGE plpgsql;
 
--- A type for use with the OBS_GetColumnData function
-CREATE TYPE cdb_observatory.OBS_ColumnData AS (colname text, tablename text, aggregate text);
 
 
 -- A function that gets the column data for multiple columns
@@ -44,82 +45,87 @@ CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetColumnData(
   column_ids text[],
   timespan text
 )
-RETURNS cdb_observatory.OBS_ColumnData[]
+RETURNS SETOF JSON
 AS $$
-DECLARE
-  result cdb_observatory.OBS_ColumnData[];
 BEGIN
+
+  -- figure out highest-weight geometry_id/timespan pair for the first data column
+  -- TODO this should be done for each data column separately
+  IF geometry_id IS NULL OR timespan IS NULL THEN
+    EXECUTE '
+      SELECT data_t.timespan timespan, geom_c.id boundary_id
+      FROM observatory.obs_table data_t,
+           observatory.obs_column_table data_ct,
+           observatory.obs_column data_c,
+           observatory.obs_column_table geoid_ct,
+           observatory.obs_column_to_column c2c,
+           observatory.obs_column geom_c
+      WHERE data_c.id = $2
+           AND data_ct.column_id = data_c.id
+           AND data_ct.table_id = data_t.id
+           AND geoid_ct.table_id = data_t.id
+           AND geoid_ct.column_id = c2c.source_id
+           AND c2c.reltype = ''geom_ref''
+           AND geom_c.id = c2c.target_id
+           AND CASE WHEN $3 IS NULL THEN True ELSE $3 = timespan END
+           AND CASE WHEN $1 IS NULL THEN True ELSE $1 = geom_c.id END
+      ORDER BY geom_c.weight DESC,
+               data_t.timespan DESC
+      LIMIT 1
+    ' INTO timespan, geometry_id
+    USING geometry_id, (column_ids)[1], timespan;
+  END IF;
+
+  RETURN QUERY
   EXECUTE '
   WITH geomref AS (
-    SELECT t.table_id id
-    FROM observatory.OBS_column_to_column c2c, observatory.OBS_column_table t
+    SELECT ct.table_id id
+    FROM observatory.OBS_column_to_column c2c,
+         observatory.OBS_column_table ct
     WHERE c2c.reltype = ''geom_ref''
       AND c2c.target_id = $1
-      AND c2c.source_id = t.column_id
+      AND c2c.source_id = ct.column_id
     ),
   column_ids as (
     select row_number() over () as no, a.column_id as column_id from (select unnest($2) as column_id) a
   )
- SELECT array_agg(ROW(colname, tablename, aggregate)::cdb_observatory.OBS_ColumnData order by column_ids.no)
- FROM column_ids, observatory.OBS_column c, observatory.OBS_column_table ct, observatory.OBS_table t
- WHERE column_ids.column_id  = c.id
-   AND c.id = ct.column_id
-   AND t.id = ct.table_id
-   AND t.timespan = $3
-   AND t.id in (SELECT id FROM geomref)
+ SELECT row_to_json(a) from (
+   select  colname,
+            tablename,
+            aggregate,
+            name,
+            type,
+            c.description,
+            $1 AS boundary_id
+           FROM column_ids, observatory.OBS_column c, observatory.OBS_column_table ct, observatory.OBS_table t
+           WHERE column_ids.column_id  = c.id
+             AND c.id = ct.column_id
+             AND t.id = ct.table_id
+             AND t.timespan = $3
+             AND t.id in (SELECT id FROM geomref)
+          order by column_ids.no
+    ) a
  '
  USING geometry_id, column_ids, timespan
- INTO result;
- RETURN result;
+ RETURN;
 
 END;
 $$ LANGUAGE plpgsql;
 
---Gets the column id for a census variable given a human readable version of it
--- Old: OBS_LOOKUP_CENSUS_HUMAN
-
-CREATE OR REPLACE FUNCTION cdb_observatory._OBS_LookupCensusHuman(
-  column_names text[],
-  -- TODO: change variable name table_name to table_id
-  table_name text DEFAULT '"us.census.acs".extract_block_group_5yr_2013_69b156927c'
-)
-RETURNS text[] as $$
-DECLARE
-  column_id text;
-  result text;
-BEGIN
-    EXECUTE format('
-      WITH col_names AS (
-        select row_number() over() as no, a.column_name as column_name from(
-          select unnest($1) as column_name
-        ) a
-      )
-      select array_agg(column_id order by col_names.no)
-      FROM observatory.OBS_column_table,col_names
-      where colname = col_names.column_name
-      and table_id = %L limit 1
-    ', table_name)
-    INTO result
-    using column_names;
-    RETURN result;
-END
-$$ LANGUAGE plpgsql;
-
-
 --Test point cause Stuart always seems to make random points in the water
 CREATE OR REPLACE FUNCTION cdb_observatory._TestPoint()
-  RETURNS geometry
+  RETURNS geometry(Point, 4326)
 AS $$
 BEGIN
   -- new york city
-  RETURN CDB_LatLng(40.704512, -73.936669);
+  RETURN ST_SetSRID(ST_Point( -73.936669, 40.704512), 4326);
 END;
 $$ LANGUAGE plpgsql;
 
 --Test polygon cause Stuart always seems to make random points in the water
 -- TODO: remove as it's not used anywhere?
 CREATE OR REPLACE FUNCTION cdb_observatory._TestArea()
-  RETURNS geometry
+  RETURNS geometry(Geometry, 4326)
 AS $$
 BEGIN
   -- Buffer NYC point by 500 meters
@@ -151,3 +157,45 @@ BEGIN
 
 END;
 $$ LANGUAGE plpgsql;
+
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetRelatedColumn(columns_ids text[], reltype text )
+RETURNS TEXT[]
+AS $$
+DECLARE
+  result TEXT[];
+BEGIN
+  EXECUTE '
+    With ids as (
+      select row_number() over() as no, id from (select unnest($1) as id) t
+    )
+    select array_agg(target_id order by no)
+    FROM  ids
+    LEFT JOIN observatory.obs_column_to_column
+    on  source_id  = id
+    where reltype = $2 or reltype is null
+  '
+  INTO result
+  using columns_ids, reltype;
+  return result;
+END;
+$$ LANGUAGE plpgsql;
+
+-- Function that replaces all non digits or letters with _ trims and lowercases the
+-- passed measure name
+
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_StandardizeMeasureName(measure_name text)
+RETURNS text
+AS $$
+DECLARE
+  result text;
+BEGIN
+  -- Turn non letter or digits to _
+  result = regexp_replace(measure_name, '[^\dA-Za-z]+','_', 'g');
+  -- Remove duplicate _'s
+  result = regexp_replace(result,'_{2,}','_', 'g');
+  -- Trim _'s from beginning and end
+  result = trim(both  '_' from result);
+  result = lower(result);
+  RETURN result;
+END;
+$$ LANGUAGE plpgsql;

src/pg/sql/42_observatory_exploration.sql

@@ -0,0 +1,122 @@
+-- return a table that contains a string match based on input
+-- TODO: implement search for timespan
+
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_SearchTables(
+  search_term text,
+  time_span text DEFAULT NULL
+)
+RETURNS table(tablename text, timespan text)
+As $$
+DECLARE
+  out_var text[];
+BEGIN
+
+  IF time_span IS NULL
+  THEN
+    RETURN QUERY
+    EXECUTE
+    'SELECT tablename::text, timespan::text
+       FROM observatory.obs_table t
+       JOIN observatory.obs_column_table ct
+         ON ct.table_id = t.id
+       JOIN observatory.obs_column c
+         ON ct.column_id = c.id
+       WHERE c.type ILIKE ''geometry''
+        AND c.id = $1'
+    USING search_term;
+    RETURN;
+  ELSE
+    RETURN QUERY
+    EXECUTE
+    'SELECT tablename::text, timespan::text
+       FROM observatory.obs_table t
+       JOIN observatory.obs_column_table ct
+         ON ct.table_id = t.id
+       JOIN observatory.obs_column c
+         ON ct.column_id = c.id
+       WHERE c.type ILIKE ''geometry''
+        AND c.id = $1
+        AND t.timespan = $2'
+    USING search_term, time_span;
+    RETURN;
+  END IF;
+
+END;
+$$ LANGUAGE plpgsql IMMUTABLE;
+
+-- Functions used to search the observatory for measures
+--------------------------------------------------------------------------------
+-- TODO allow the user to specify the boundary to search for measures
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_Search(
+  search_term text,
+  relevant_boundary text DEFAULT null
+)
+RETURNS TABLE(id text, description text, name text, aggregate text, source text)  as $$
+DECLARE
+  boundary_term text;
+BEGIN
+  IF relevant_boundary then
+    boundary_term = '';
+  else
+    boundary_term = '';
+  END IF;
+
+  RETURN QUERY
+  EXECUTE format($string$
+              SELECT id::text, description::text,
+                name::text,
+                  aggregate::text,
+                  NULL::TEXT source -- TODO use tags
+                  FROM observatory.OBS_column
+                  where name ilike     '%%' || %L || '%%'
+                  or description ilike '%%' || %L || '%%'
+                  %s
+                $string$, search_term, search_term,boundary_term);
+  RETURN;
+END
+$$ LANGUAGE plpgsql;
+
+
+-- Functions to return the geometry levels that a point is part of
+--------------------------------------------------------------------------------
+-- TODO add test response
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetAvailableBoundaries(
+  geom geometry(Geometry, 4326),
+  timespan text DEFAULT null)
+RETURNS TABLE(boundary_id text, description text, time_span text, tablename text)  as $$
+DECLARE
+  timespan_query TEXT DEFAULT '';
+BEGIN
+
+  IF timespan != NULL
+  THEN
+    timespan_query = format('AND timespan = %L', timespan);
+  END IF;
+
+  RETURN QUERY
+  EXECUTE
+  $string$
+      SELECT
+        column_id::text As column_id,
+        obs_column.description::text As description,
+        timespan::text As timespan,
+        tablename::text As tablename
+      FROM
+        observatory.OBS_table,
+        observatory.OBS_column_table,
+        observatory.OBS_column
+      WHERE
+        observatory.OBS_column_table.column_id = observatory.obs_column.id AND
+        observatory.OBS_column_table.table_id = observatory.obs_table.id
+      AND
+        observatory.OBS_column.type = 'Geometry'
+      AND
+        $1 && bounds::box2d
+  $string$ || timespan_query
+  USING geom;
+  RETURN;
+END
+$$ LANGUAGE plpgsql;

src/pg/sql/44_observatory_geometries.sql

@@ -0,0 +1,574 @@
+-- Data Observatory -- Welcome to the Future
+-- These Data Observatory functions provide access to boundary polyons (and
+--   their ids) such as those available through the US Census Tiger, Who's on
+--   First, the Spanish Census, and so on
+
+
+-- OBS_GetBoundary
+--
+-- Returns the boundary polygon(s) that overlap with the input point geometry.
+-- From an input point geometry, find the boundary which intersects with the
+--   centroid of the input geometry
+-- Inputs:
+--   geom geometry: input point geometry
+--   boundary_id text: source id of boundaries
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   boundary geometry: geometry boundary that intersects with geom, is at the
+--                      resolution requested with boundary_id, and time_span
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundary(
+  geom geometry(Point, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL)
+RETURNS geometry(Geometry, 4326)
+AS $$
+DECLARE
+  boundary geometry(Geometry, 4326);
+  target_table text;
+BEGIN
+
+  -- TODO: Check if SRID = 4326, if not transform?
+
+  -- if not a point, raise error
+  IF ST_GeometryType(geom) != 'ST_Point'
+  THEN
+    RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_Point''', ST_GeometryType(geom);
+  END IF;
+
+  -- choose appropriate table based on time_span
+  IF time_span IS NULL
+  THEN
+    SELECT x.target_tables INTO target_table
+    FROM cdb_observatory._OBS_SearchTables(boundary_id,
+                                           time_span) As x(target_tables,
+                                                           timespans)
+    ORDER BY x.timespans DESC
+    LIMIT 1;
+  ELSE
+    -- TODO: modify for only one table returned instead of arbitrarily choosing
+    --       one with LIMIT 1 (could be conflict between clipped vs non-clipped
+    --       boundaries in the metadata tables)
+    SELECT x.target_tables INTO target_table
+    FROM cdb_observatory._OBS_SearchTables(boundary_id,
+                            time_span) As x(target_tables,
+                                            timespans)
+    WHERE x.timespans = time_span
+    LIMIT 1;
+  END IF;
+
+  -- if no tables are found, raise notice and return null
+  IF target_table IS NULL
+  THEN
+    RAISE NOTICE 'No boundaries found for ''%'' in ''%''', ST_AsText(geom), boundary_id;
+    RETURN NULL::geometry;
+  END IF;
+
+  RAISE NOTICE 'target_table: %', target_table;
+
+  -- return the first boundary in intersections
+  EXECUTE format(
+    'SELECT the_geom
+     FROM observatory.%I
+     WHERE ST_Intersects($1, the_geom)
+     LIMIT 1', target_table)
+  INTO boundary
+  USING geom;
+
+  RETURN boundary;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- OBS_GetBoundaryId
+--
+-- retrieves the boundary identifier (e.g., '36047' = Kings County/Brooklyn, NY)
+--   corresponding to the location geom and boundary types (e.g.,
+--   us.census.tiger.county)
+
+-- Inputs:
+--   geom geometry: location where the boundary is requested to overlap with
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   geometry_id text: identifier of the geometry which overlaps with the input
+--                     point geom in the table corresponding to boundary_id and
+--                     time_span
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundaryId(
+  geom geometry(Point, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL
+)
+RETURNS text
+AS $$
+DECLARE
+  output_id text;
+  target_table text;
+  geoid_colname text;
+BEGIN
+
+  -- If not point, raise error
+  IF ST_GeometryType(geom) != 'ST_Point'
+  THEN
+    RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_Point''', ST_GeometryType(geom);
+  END IF;
+
+  -- choose appropriate table based on time_span
+  IF time_span IS NULL
+  THEN
+    SELECT x.target_tables INTO target_table
+    FROM cdb_observatory._OBS_SearchTables(boundary_id,
+                            time_span) As x(target_tables,
+                                                timespans)
+    ORDER BY x.timespans DESC
+    LIMIT 1;
+  ELSE
+    SELECT x.target_tables INTO target_table
+    FROM cdb_observatory._OBS_SearchTables(boundary_id,
+                            time_span) As x(target_tables,
+                                            timespans)
+    WHERE x.timespans = time_span
+    LIMIT 1;
+  END IF;
+
+  -- if no tables are found, raise notice and return null
+  IF target_table IS NULL
+  THEN
+    RAISE NOTICE 'Warning: No boundaries found for ''%''', boundary_id;
+    RETURN NULL::text;
+  END IF;
+
+  EXECUTE
+    format('SELECT ct.colname
+              FROM observatory.obs_column_to_column c2c,
+                   observatory.obs_column_table ct,
+                   observatory.obs_table t
+             WHERE c2c.reltype = ''geom_ref''
+               AND ct.column_id = c2c.source_id
+               AND ct.table_id = t.id
+               AND t.tablename = %L'
+   , target_table)
+  INTO geoid_colname;
+
+  RAISE NOTICE 'target_table: %, geoid_colname: %', target_table, geoid_colname;
+
+  -- return name of geometry id column
+  EXECUTE format(
+    'SELECT %I
+     FROM observatory.%I
+     WHERE ST_Intersects($1, the_geom)
+     LIMIT 1', geoid_colname, target_table)
+  INTO output_id
+  USING geom;
+
+  RETURN output_id;
+
+END;
+$$ LANGUAGE plpgsql;
+
+
+-- OBS_GetBoundaryById
+--
+-- Given a geometry reference (e.g., geoid for US Census), and it's geometry
+--  level (see OBS_ListGeomColumns() for all available boundary ids), give back
+--  the boundary that corresponds to that geometry_id, boundary_id, and
+--   time_span
+
+-- Inputs:
+--   geometry_id text: geometry id of the requested boundary
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   boundary geometry: geometry boundary that matches geometry_id, is at the
+--                      resolution requested with boundary_id, and time_span
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundaryById(
+  geometry_id text,            -- ex: '36047'
+  boundary_id text,            -- ex: 'us.census.tiger.county'
+  time_span text DEFAULT NULL  -- ex: '2009'
+)
+RETURNS geometry(geometry, 4326)
+AS $$
+DECLARE
+  boundary geometry(geometry, 4326);
+  target_table text;
+  geoid_colname text;
+  geom_colname text;
+BEGIN
+
+  SELECT * INTO geoid_colname, target_table, geom_colname
+  FROM cdb_observatory._OBS_GetGeometryMetadata(boundary_id);
+
+  RAISE NOTICE '%', target_table;
+
+  IF target_table IS NULL
+  THEN
+    RAISE NOTICE 'No geometries found';
+    RETURN NULL::geometry;
+  END IF;
+
+  -- retrieve boundary
+  EXECUTE
+    format(
+    'SELECT %I
+     FROM observatory.%I
+     WHERE %I = $1
+     LIMIT 1', geom_colname, target_table, geoid_colname)
+  INTO boundary
+  USING geometry_id;
+
+  RETURN boundary;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- _OBS_GetBoundariesByGeometry
+-- internal function for retrieving geometries based on an input geometry
+--  see OBS_GetBoundariesByGeometry or OBS_GetBoundariesByPointAndRadius for
+--  more information
+
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetBoundariesByGeometry(
+  geom geometry(Geometry, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+DECLARE
+  boundary geometry(Geometry, 4326);
+  geom_colname text;
+  geoid_colname text;
+  target_table text;
+BEGIN
+
+  -- check inputs
+  IF lower(overlap_type) NOT IN ('contains', 'intersects', 'within')
+  THEN
+    -- recognized overlap type (map to ST_Contains, ST_Intersects, and ST_Within)
+    RAISE EXCEPTION 'Overlap type ''%'' is not an accepted type (choose intersects, within, or contains)', overlap_type;
+  ELSIF ST_GeometryType(geom) NOT IN ('ST_Polygon', 'ST_MultiPolygon')
+  THEN
+      RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_MultiPolygon'' or ''ST_Polygon''', ST_GeometryType(geom);
+  END IF;
+
+  -- TODO: add timespan in search
+  -- TODO: add overlap info in search
+  SELECT * INTO geoid_colname, target_table, geom_colname
+  FROM cdb_observatory._OBS_GetGeometryMetadata(boundary_id);
+
+  -- if no tables are found, raise notice and return null
+  IF target_table IS NULL
+  THEN
+    RAISE NOTICE 'No boundaries found for bounding box ''%'' in ''%''', ST_AsText(geom), boundary_id;
+    RETURN QUERY SELECT NULL::geometry, NULL::text;
+    RETURN;
+  END IF;
+
+  RAISE NOTICE 'target_table: %', target_table;
+
+  -- return first boundary in intersections
+  RETURN QUERY
+  EXECUTE format(
+    'SELECT %I, %I
+     FROM observatory.%I
+     WHERE ST_%s($1, the_geom)
+     ', geom_colname, geoid_colname, target_table, overlap_type)
+  USING geom;
+  RETURN;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- OBS_GetBoundariesByGeometry
+--
+-- Given a bounding box (or a polygon), and it's geometry level (see
+--  OBS_ListGeomColumns() for all available boundary ids), give back the
+--  boundaries that are contained within the bounding box polygon and the
+--  associated geometry ids
+
+-- Inputs:
+--   geom geometry: bounding box (or polygon) of the region of interest
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   table with the following columns
+--     boundary geometry: geometry boundary that is contained within the input
+--                          bounding box at the requested geometry level
+--                          with boundary_id, and time_span
+--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundariesByGeometry(
+  geom geometry(Geometry, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+BEGIN
+
+  RETURN QUERY SELECT *
+               FROM cdb_observatory._OBS_GetBoundariesByGeometry(
+                          geom,
+                          boundary_id,
+                          time_span,
+                          overlap_type
+                        );
+  RETURN;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- OBS_GetBoundariesByPointAndRadius
+--
+-- Given a point and radius, and it's geometry level (see
+--  OBS_ListGeomColumns() for all available boundary ids), give back the
+--  boundaries that are contained within the point buffered by radius meters and
+--  the associated geometry ids
+
+-- Inputs:
+--   geom geometry: point geometry centered on area of interest
+--   radius numeric: radius (in meters) of a circle centered on geom for
+--                   selecting polygons
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   table with the following columns
+--     boundary geometry: geometry boundary that is contained within the input
+--                          bounding box at the requested geometry level
+--                          with boundary_id, and time_span
+--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
+--
+-- TODO: move to ST_DWithin instead of buffer + intersects?
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetBoundariesByPointAndRadius(
+  geom geometry(Point, 4326), -- point
+  radius numeric, -- radius in meters
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+DECLARE
+  circle_boundary geometry(Geometry, 4326);
+BEGIN
+
+  IF ST_GeometryType(geom) != 'ST_Point'
+  THEN
+    RAISE EXCEPTION 'Input geometry ''%'' is not a point', ST_AsText(geom);
+  ELSE
+    circle_boundary := ST_Buffer(geom::geography, radius)::geometry;
+  END IF;
+
+  RETURN QUERY SELECT *
+               FROM cdb_observatory._OBS_GetBoundariesByGeometry(
+                        circle_boundary,
+                        boundary_id,
+                        time_span);
+  RETURN;
+END;
+$$ LANGUAGE plpgsql;
+
+-- _OBS_GetPointsByGeometry
+
+
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetPointsByGeometry(
+  geom geometry(Geometry, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+DECLARE
+  boundary geometry(Geometry, 4326);
+  geom_colname text;
+  geoid_colname text;
+  target_table text;
+BEGIN
+
+  IF lower(overlap_type) NOT IN ('contains', 'within', 'intersects')
+  THEN
+    RAISE EXCEPTION 'Overlap type ''%'' is not an accepted type (choose intersects, within, or contains)', overlap_type;
+  ELSIF ST_GeometryType(geom) NOT IN ('ST_Polygon', 'ST_MultiPolygon')
+  THEN
+      RAISE EXCEPTION 'Invalid geometry type (%), expecting ''ST_MultiPolygon'' or ''ST_Polygon''', ST_GeometryType(geom);
+  END IF;
+
+  SELECT * INTO geoid_colname, target_table, geom_colname
+  FROM cdb_observatory._OBS_GetGeometryMetadata(boundary_id);
+
+  -- if no tables are found, raise notice and return null
+  IF target_table IS NULL
+  THEN
+    RAISE NOTICE 'No boundaries found for bounding box ''%'' in ''%''', ST_AsText(geom), boundary_id;
+    RETURN QUERY SELECT NULL::geometry, NULL::text;
+    RETURN;
+  END IF;
+
+  RAISE NOTICE 'target_table: %', target_table;
+
+  -- return first boundary in intersections
+  RETURN QUERY
+  EXECUTE format(
+    'SELECT ST_PointOnSurface(%I) As %s, %I
+     FROM observatory.%I
+     WHERE ST_%s($1, the_geom)
+     ', geom_colname, geom_colname, geoid_colname, target_table, overlap_type)
+  USING geom;
+  RETURN;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- OBS_GetPointsByGeometry
+--
+-- Given a polygon, and it's geometry level (see
+--  OBS_ListGeomColumns() for all available boundary ids), give back a point
+--  which lies in a boundary from the requested geometry level that is contained
+--  within the bounding box polygon and the associated geometry ids
+--
+-- Inputs:
+--   geom geometry: bounding box (or polygon) of the region of interest
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   table with the following columns
+--     boundary geometry: point that lies on a boundary that is contained within
+--                          the input bounding box at the requested geometry
+--                          level with boundary_id, and time_span
+--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetPointsByGeometry(
+  geom geometry(Geometry, 4326),
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+BEGIN
+
+  RETURN QUERY SELECT *
+               FROM cdb_observatory._OBS_GetPointsByGeometry(
+                      geom,
+                      boundary_id,
+                      time_span,
+                      overlap_type);
+  RETURN;
+
+END;
+$$ LANGUAGE plpgsql;
+
+-- OBS_GetBoundariesByPointAndRadius
+--
+-- Given a point and radius, and it's geometry level (see
+--  OBS_ListGeomColumns() for all available boundary ids), give back the
+--  boundaries that are contained within the point buffered by radius meters and
+--  the associated geometry ids
+
+-- Inputs:
+--   geom geometry: point geometry centered on area of interest
+--   radius numeric: radius (in meters) of a circle centered on geom for
+--                   selecting polygons
+--   boundary_id text: source id of boundaries (e.g., us.census.tiger.county)
+--                     see function OBS_ListGeomColumns for all avaiable
+--                     boundary ids
+--   time_span text: time span that the geometries were collected (optional)
+--
+-- Output:
+--   table with the following columns
+--     boundary geometry: geometry boundary that is contained within the input
+--                          bounding box at the requested geometry level
+--                          with boundary_id, and time_span
+--     geom_refs text: geometry identifiers (e.g., geoid for the US Census)
+--
+
+CREATE OR REPLACE FUNCTION cdb_observatory.OBS_GetPointsByPointAndRadius(
+  geom geometry(Point, 4326), -- point
+  radius numeric, -- radius in meters
+  boundary_id text,
+  time_span text DEFAULT NULL,
+  overlap_type text DEFAULT 'intersects')
+RETURNS TABLE(the_geom geometry, geom_refs text)
+AS $$
+DECLARE
+  circle_boundary geometry(Geometry, 4326);
+BEGIN
+
+  IF ST_GeometryType(geom) != 'ST_Point'
+  THEN
+    RAISE EXCEPTION 'Input geometry ''%'' is not a point', ST_AsText(geom);
+  ELSE
+    circle_boundary := ST_Buffer(geom::geography, radius)::geometry;
+  END IF;
+
+  RETURN QUERY SELECT *
+               FROM cdb_observatory._OBS_GetPointsByGeometry(
+                        ST_Buffer(geom::geography, radius)::geometry,
+                        boundary_id,
+                        time_span,
+                        overlap_type);
+  RETURN;
+END;
+$$ LANGUAGE plpgsql;
+
+
+-- _OBS_GetGeometryMetadata()
+-- TODO: add timespan in search
+-- TODO: add choice of clipped versus not clipped
+CREATE OR REPLACE FUNCTION cdb_observatory._OBS_GetGeometryMetadata(boundary_id text)
+RETURNS table(geoid_colname text, target_table text, geom_colname text)
+AS $$
+BEGIN
+
+  RETURN QUERY
+  EXECUTE
+  format($string$
+    SELECT geoid_ct.colname::text As geoid_colname,
+           tablename::text,
+           geom_ct.colname::text As geom_colname
+    FROM observatory.obs_column_table As geoid_ct,
+         observatory.obs_table As geom_t,
+         observatory.obs_column_table As geom_ct,
+         observatory.obs_column As geom_c
+    WHERE geoid_ct.column_id
+       IN (
+         SELECT source_id
+         FROM observatory.obs_column_to_column
+         WHERE reltype = 'geom_ref'
+           AND target_id = '%s'
+         )
+      AND geoid_ct.table_id = geom_t.id AND
+          geom_t.id = geom_ct.table_id AND
+          geom_ct.column_id = geom_c.id AND
+          geom_c.type ILIKE 'geometry' AND
+          geom_c.id = '%s'
+    $string$, boundary_id, boundary_id);
+    --  AND geom_t.timespan = '%s' <-- put in requested year
+    -- TODO: filter by clipped vs. not so appropriate tablename are unique
+    --       so the limit 1 can be removed
+    RETURN;
+
+END;
+$$ LANGUAGE plpgsql;

src/pg/test/expected/02_load_tables_test.out

@@ -1,4 +0,0 @@
-SET client_min_messages TO WARNING;
-\set ECHO none
-Loading fixtures...
-Done.

src/pg/test/expected/40_observatory_utility_test.out

@@ -1,152 +1,29 @@
-\i test/sql/load_fixtures.sql
+\pset format unaligned
+\set ECHO all
+\i test/fixtures/load_fixtures.sql
 SET client_min_messages TO WARNING;
 \set ECHO none
-Loading obs_table.sql fixture file...
-Done.
-Loading obs_column.sql fixture file...
-Done.
-Loading obs_column_table.sql fixture file...
-Done.
-Loading obs_column_to_column.sql fixture file...
-Done.
-Loading obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1.sql fixture file...
-Done.
-Loading obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb.sql fixture file...
-Done.
-Loading obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql fixture file...
-Done.
-Loading obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql fixture file...
-Done.
-Loading obs_11ee8b82c877c073438bc935a91d3dfccef875d1.sql fixture file...
-Done.
-Loading obs_d34555209878e8c4b37cf0b2b3d072ff129ec470.sql fixture file...
-Done.
--- OBS_GeomTable
--- get table with known geometry_id
--- should give back a table like obs_{hex hash}
-SELECT
-  cdb_observatory._OBS_GeomTable(
-    CDB_LatLng(40.7128,-74.0059),
-    '"us.census.tiger".census_tract'
-  );
-                _obs_geomtable                
-----------------------------------------------
- obs_a92e1111ad3177676471d66bb8036e6d057f271b
+_obs_geomtable_with_returned_table
+t
 (1 row)
-
--- get null for unknown geometry_id
--- should give back null
-SELECT
-  cdb_observatory._OBS_GeomTable(
-    CDB_LatLng(40.7128,-74.0059),
-    '"us.census.tiger".nonexistant_id' -- not in catalog
-  );
- _obs_geomtable 
-----------------
- 
+_obs_geomtable_with_null_response
+t
 (1 row)
-
--- future test: give back nulls when geometry doesn't intersect
--- SELECT
---   cdb_observatory._OBS_GeomTable(
---     CDB_LatLng(0,0), -- should give back null since it's in the ocean?
---     '"us.census.tiger".census_tract'
---   );
--- OBS_GetColumnData
--- should give back:
---  colname   | tablename       | aggregate
--- -----------|-----------------|-----------
---  geoid     | obs_{hex table} | null
---  total_pop | obs_{hex table} | sum
-SELECT
-  (unnest(cdb_observatory._OBS_GetColumnData(
-    '"us.census.tiger".census_tract',
-    Array['"us.census.tiger".census_tract_geoid', '"us.census.acs".B01001001'],
-    '2009 - 2013'
-  ))).*
-ORDER BY colname, tablename ASC;
-  colname  |                  tablename                   | aggregate 
------------+----------------------------------------------+-----------
- geoid     | obs_11ee8b82c877c073438bc935a91d3dfccef875d1 | 
- geoid     | obs_ab038198aaab3f3cb055758638ee4de28ad70146 | 
- geoid     | obs_d34555209878e8c4b37cf0b2b3d072ff129ec470 | 
- total_pop | obs_ab038198aaab3f3cb055758638ee4de28ad70146 | sum
-(4 rows)
-
--- should be null-valued
-SELECT
-  (unnest(cdb_observatory._OBS_GetColumnData(
-    '"us.census.tiger".census_tract',
-    Array['"us.census.tiger".baloney'], -- entry not in catalog
-    '2009 - 2013'
-  ))).*
-ORDER BY 1 ASC;
- colname | tablename | aggregate 
----------+-----------+-----------
-(0 rows)
-
--- OBS_LookupCensusHuman
--- should give back: {"\"us.census.acs\".B19083001"}
-SELECT
-  cdb_observatory._OBS_LookupCensusHuman(
-    Array['gini_index']
-  );
-     _obs_lookupcensushuman      
----------------------------------
- {"\"us.census.acs\".B19083001"}
+test_get_obs_column_with_geoid_and_census_1|test_get_obs_column_with_geoid_and_census_2
+t|t
 (1 row)
-
--- should be empty array
-SELECT
-  cdb_observatory._OBS_LookupCensusHuman(
-    Array['cookies']
-  );
- _obs_lookupcensushuman 
-------------------------
- 
+obs_getcolumndata_missing_measure
+t
 (1 row)
-
--- OBS_BuildSnapshotQuery
--- Should give back: SELECT  vals[1] As total_pop, vals[2] As male_pop, vals[3] As female_pop, vals[4] As median_age
-SELECT
-  cdb_observatory._OBS_BuildSnapshotQuery(
-    Array['total_pop','male_pop','female_pop','median_age']
-  );
-                                     _obs_buildsnapshotquery                                     
--------------------------------------------------------------------------------------------------
- SELECT  vals[1] As total_pop, vals[2] As male_pop, vals[3] As female_pop, vals[4] As median_age
+_obs_buildsnapshotquery_test_1
+t
 (1 row)
-
--- should give back: SELECT  vals[1] As mandarin_orange
-SELECT
-  cdb_observatory._OBS_BuildSnapshotQuery(
-    Array['mandarin_orange']
-  );
-      _obs_buildsnapshotquery       
-------------------------------------
- SELECT  vals[1] As mandarin_orange
+_obs_buildsnapshotquery_test_2
+t
+(1 row)
+_obs_getrelatedcolumn_test
+t
+(1 row)
+_obs_standardizemeasurename_test
+t
 (1 row)
-
-\i test/sql/drop_fixtures.sql
-SET client_min_messages TO NOTICE;
-\set ECHO none
-Dropping obs_table.sql fixture table...
-Done.
-Dropping obs_column.sql fixture table...
-Done.
-Dropping obs_column_table.sql fixture table...
-Done.
-Dropping obs_column_to_column.sql fixture table...
-Done.
-Dropping obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1 fixture table...
-Done.
-Dropping obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb fixture table...
-Done.
-Dropping obs_ab038198aaab3f3cb055758638ee4de28ad70146 fixture table...
-Done.
-Dropping obs_a92e1111ad3177676471d66bb8036e6d057f271b fixture table...
-Done.
-Dropping obs_11ee8b82c877c073438bc935a91d3dfccef875d1 fixture table...
-Done.
-Dropping obs_d34555209878e8c4b37cf0b2b3d072ff129ec470 fixture table...
-Done.

src/pg/test/expected/41_observatory_augmentation_test.out

@@ -1,113 +1,78 @@
-\i test/sql/load_fixtures.sql
+\i test/fixtures/load_fixtures.sql
 SET client_min_messages TO WARNING;
 \set ECHO none
-Loading obs_table.sql fixture file...
-Done.
-Loading obs_column.sql fixture file...
-Done.
-Loading obs_column_table.sql fixture file...
-Done.
-Loading obs_column_to_column.sql fixture file...
-Done.
-Loading obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1.sql fixture file...
-Done.
-Loading obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb.sql fixture file...
-Done.
-Loading obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql fixture file...
-Done.
-Loading obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql fixture file...
-Done.
-Loading obs_11ee8b82c877c073438bc935a91d3dfccef875d1.sql fixture file...
-Done.
-Loading obs_d34555209878e8c4b37cf0b2b3d072ff129ec470.sql fixture file...
-Done.
-    total_pop     |     male_pop     |    female_pop    | median_age |    white_pop     |    black_pop     |    asian_pop     |   hispanic_pop   | amerindian_pop | other_race_pop | two_or_more_races_pop | not_hispanic_pop |    households    | pop_25_years_over | high_school_diploma | less_one_year_college | one_year_more_college | associates_degree | bachelors_degree |  masters_degree  | median_income | gini_index | income_per_capita |  housing_units   | vacant_housing_units | vacant_housing_units_for_rent | vacant_housing_units_for_sale | median_rent | percent_income_spent_on_rent | owner_occupied_housing_units | million_dollar_housing_units | mortgaged_housing_units | commuters_16_over | commute_less_10_mins | commute_10_14_mins | commute_15_19_mins | commute_20_24_mins | commute_25_29_mins | commute_30_34_mins | commute_35_44_mins | commute_45_59_mins | commute_60_more_mins | aggregate_travel_time_to_work | income_less_10000 | income_10000_14999 | income_15000_19999 | income_20000_24999 | income_25000_29999 | income_30000_34999 | income_35000_39999 | income_40000_44999 | income_45000_49999 | income_50000_59999 | income_60000_74999 | income_75000_99999 | income_100000_124999 | income_125000_149999 | income_150000_199999 | income_200000_or_more | land_area 
-------------------+------------------+------------------+------------+------------------+------------------+------------------+------------------+----------------+----------------+-----------------------+------------------+------------------+-------------------+---------------------+-----------------------+-----------------------+-------------------+------------------+------------------+---------------+------------+-------------------+------------------+----------------------+-------------------------------+-------------------------------+-------------+------------------------------+------------------------------+------------------------------+-------------------------+-------------------+----------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+----------------------+-------------------------------+-------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+----------------------+----------------------+----------------------+-----------------------+-----------
- 9516.27915900609 | 6152.51885204623 | 3363.76030695986 |       28.8 | 5301.51624447348 | 149.500458087105 | 230.000704749392 | 3835.26175169611 |              0 |              0 |                     0 | 5681.01740730998 | 3323.51018362871 |  7107.02177675621 |      1040.753188991 |      69.0002114248176 |      793.502431385402 |  327.751004267883 |  2742.7584041365 | 931.502854235037 |         66304 |     0.3494 |             28291 | 3662.76122313407 |     339.251039505353 |              120.750369993431 |                             0 |        1764 |                         35.3 |             339.251039505353 |                            0 |        224.250687130657 |  6549.27006773893 |     327.751004267883 |    28.750088093674 |   201.250616655718 |   621.001902823358 |   373.751145217762 |    1851.5056732326 |   1414.50433420876 |   1115.50341803455 |     615.251885204623 |                               |   57.500176187348 |                  0 |   212.750651893187 |   408.251250930171 |                  0 |    155.25047570584 |   109.250334755961 |   92.0002818997568 |   63.2501938060828 |   184.000563799514 |   621.001902823358 |   552.001691398541 |     327.751004267883 |     333.501021886618 |     126.500387612166 |                       |          
+obs_getdemographicsnapshot_test_no_returns
+t
 (1 row)
-
-      dimension       |           dimension_value           
-----------------------+-------------------------------------
- {total_pop,male_pop} | {9516.27915900609,6152.51885204623}
+obs_get_median_income_at_test_point
+t
 (1 row)
-
-       dimension       | dimension_value 
------------------------+-----------------
- {female_pop,male_pop} | {NULL,NULL}
+obs_get_median_income_at_null_island
+t
 (1 row)
-
-       dimension       | dimension_value 
------------------------+-----------------
- {female_pop,male_pop} | {}
+obs_getpoints_for_test_point_value|obs_getpoints_for_test_point_name|obs_getpoints_for_test_point_tablename|obs_getpoints_for_test_point_aggregate|obs_getpoints_for_test_point_type|obs_getpoints_for_test_point_description
+t|t|t|t|t|t
 (1 row)
-
-    names     |   vals   
---------------+----------
- {gini_index} | {0.3494}
+obs_getpoints_for_null_island
+t
 (1 row)
-
-    names     | vals 
---------------+------
- {gini_index} | {}
+obs_getpolygons_for_test_point
+t
 (1 row)
-
-   _obs_getpoints   
---------------------
- {4809.33511352425}
+obs_getpolygons_for_null_island
+t
 (1 row)
-
- _obs_getpoints 
-----------------
- 
+test_point_segmentation
+t
 (1 row)
-
-  _obs_getpolygons  
---------------------
- {1570.72353789469}
+null_island_segmentation
+t
 (1 row)
-
- _obs_getpolygons 
-------------------
- {NULL}
+getcategories_at_test_point_1
+t
 (1 row)
-
-        segment_name         | total_pop_quantile | male_pop_quantile | female_pop_quantile | median_age_quantile | white_pop_quantile | black_pop_quantile | asian_pop_quantile | hispanic_pop_quantile | not_us_citizen_pop_quantile | workers_16_and_over_quantile | commuters_by_car_truck_van_quantile | commuters_by_public_transportation_quantile | commuters_by_bus_quantile | commuters_by_subway_or_elevated_quantile | walked_to_work_quantile | worked_at_home_quantile | children_quantile  | households_quantile | population_3_years_over_quantile | in_school_quantile | in_grades_1_to_4_quantile | in_grades_5_to_8_quantile | in_grades_9_to_12_quantile | in_undergrad_college_quantile | pop_25_years_over_quantile | high_school_diploma_quantile | bachelors_degree_quantile | masters_degree_quantile | pop_5_years_over_quantile | speak_only_english_at_home_quantile | speak_spanish_at_home_quantile | pop_determined_poverty_status_quantile | poverty_quantile  | median_income_quantile | gini_index_quantile | income_per_capita_quantile | housing_units_quantile | vacant_housing_units_quantile | vacant_housing_units_for_rent_quantile | vacant_housing_units_for_sale_quantile | median_rent_quantile | percent_income_spent_on_rent_quantile | owner_occupied_housing_units_quantile | million_dollar_housing_units_quantile 
------------------------------+--------------------+-------------------+---------------------+---------------------+--------------------+--------------------+--------------------+-----------------------+-----------------------------+------------------------------+-------------------------------------+---------------------------------------------+---------------------------+------------------------------------------+-------------------------+-------------------------+--------------------+---------------------+----------------------------------+--------------------+---------------------------+---------------------------+----------------------------+-------------------------------+----------------------------+------------------------------+---------------------------+-------------------------+---------------------------+-------------------------------------+--------------------------------+----------------------------------------+-------------------+------------------------+---------------------+----------------------------+------------------------+-------------------------------+----------------------------------------+----------------------------------------+----------------------+---------------------------------------+---------------------------------------+---------------------------------------
- Wealthy, urban without Kids |  0.234783783783784 | 0.422405405405405 |  0.0987567567567568 |              0.0715 |  0.295310810810811 |  0.407189189189189 |  0.625608108108108 |     0.795202702702703 |           0.703797297297297 |             0.59227027027027 |                  0.0180540540540541 |                           0.993756756756757 |         0.728162162162162 |                        0.995972972972973 |       0.929135135135135 |       0.625432432432432 | 0.0386081081081081 |   0.157121621621622 |                0.241878378378378 |  0.173783783783784 |        0.0380675675675676 |        0.0308108108108108 |         0.0486216216216216 |             0.479743243243243 |          0.297675675675676 |            0.190351351351351 |         0.802513513513514 |       0.757148648648649 |         0.255405405405405 |                   0.196094594594595 |              0.816851351351351 |                      0.252513513513514 | 0.560054054054054 |      0.777472972972973 |   0.336932432432432 |          0.655378378378378 |      0.141810810810811 |             0.362824324324324 |                      0.463837837837838 |                                      0 |    0.939040540540541 |                     0.419445945945946 |                    0.0387972972972973 |                                     0
+getcategories_at_null_island
+t
 (1 row)
-
- segment_name | total_pop_quantile | male_pop_quantile | female_pop_quantile | median_age_quantile | white_pop_quantile | black_pop_quantile | asian_pop_quantile | hispanic_pop_quantile | not_us_citizen_pop_quantile | workers_16_and_over_quantile | commuters_by_car_truck_van_quantile | commuters_by_public_transportation_quantile | commuters_by_bus_quantile | commuters_by_subway_or_elevated_quantile | walked_to_work_quantile | worked_at_home_quantile | children_quantile | households_quantile | population_3_years_over_quantile | in_school_quantile | in_grades_1_to_4_quantile | in_grades_5_to_8_quantile | in_grades_9_to_12_quantile | in_undergrad_college_quantile | pop_25_years_over_quantile | high_school_diploma_quantile | bachelors_degree_quantile | masters_degree_quantile | pop_5_years_over_quantile | speak_only_english_at_home_quantile | speak_spanish_at_home_quantile | pop_determined_poverty_status_quantile | poverty_quantile | median_income_quantile | gini_index_quantile | income_per_capita_quantile | housing_units_quantile | vacant_housing_units_quantile | vacant_housing_units_for_rent_quantile | vacant_housing_units_for_sale_quantile | median_rent_quantile | percent_income_spent_on_rent_quantile | owner_occupied_housing_units_quantile | million_dollar_housing_units_quantile 
---------------+--------------------+-------------------+---------------------+---------------------+--------------------+--------------------+--------------------+-----------------------+-----------------------------+------------------------------+-------------------------------------+---------------------------------------------+---------------------------+------------------------------------------+-------------------------+-------------------------+-------------------+---------------------+----------------------------------+--------------------+---------------------------+---------------------------+----------------------------+-------------------------------+----------------------------+------------------------------+---------------------------+-------------------------+---------------------------+-------------------------------------+--------------------------------+----------------------------------------+------------------+------------------------+---------------------+----------------------------+------------------------+-------------------------------+----------------------------------------+----------------------------------------+----------------------+---------------------------------------+---------------------------------------+---------------------------------------
-              |                    |                   |                     |                     |                    |                    |                    |                       |                             |                              |                                     |                                             |                           |                                          |                         |                         |                   |                     |                                  |                    |                           |                           |                            |                               |                            |                              |                           |                         |                           |                                     |                                |                                        |                  |                        |                     |                            |                        |                               |                                        |                                        |                      |                                       |                                       |                                      
+obs_getmeasure_zhvi_point_test
+t
 (1 row)
-
- names |           categories            
--------+---------------------------------
- {X10} | {"Wealthy, urban without Kids"}
+obs_getmeasure_zhvi_point_default_latest_test
+t
 (1 row)
-
- names | categories 
--------+------------
- {X10} | 
+obs_getmeasure_total_pop_point_test
+t
+(1 row)
+obs_getmeasure_total_pop_polygon_test
+t
+(1 row)
+obs_getmeasure_total_male_point_denominator
+t
+(1 row)
+obs_getmeasure_total_male_poly_denominator
+t
+(1 row)
+obs_getcategory_point
+t
+(1 row)
+obs_getcategory_polygon
+t
+(1 row)
+obs_getpopulation
+t
+(1 row)
+obs_getpopulation_polygon_test
+t
+(1 row)
+obs_getuscensusmeasure_point_male_pop
+t
+(1 row)
+obs_getuscensusmeasure
+t
+(1 row)
+obs_getuscensuscategory_point
+t
+(1 row)
+obs_getuscensuscategory_polygon
+t
 (1 row)
-
-Dropping obs_table.sql fixture table...
-Done.
-Dropping obs_column.sql fixture table...
-Done.
-Dropping obs_column_table.sql fixture table...
-Done.
-Dropping obs_column_to_column.sql fixture table...
-Done.
-Dropping obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1 fixture table...
-Done.
-Dropping obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb fixture table...
-Done.
-Dropping obs_ab038198aaab3f3cb055758638ee4de28ad70146 fixture table...
-Done.
-Dropping obs_a92e1111ad3177676471d66bb8036e6d057f271b fixture table...
-Done.
-Dropping obs_11ee8b82c877c073438bc935a91d3dfccef875d1 fixture table...
-Done.
-Dropping obs_d34555209878e8c4b37cf0b2b3d072ff129ec470 fixture table...
-Done.

src/pg/test/expected/42_observatory_exploration_test.out

@@ -0,0 +1,70 @@
+\i test/fixtures/load_fixtures.sql
+SET client_min_messages TO WARNING;
+\set ECHO none
+_obs_searchtables_tables_match|_obs_searchtables_timespan_matches
+t|t
+(1 row)
+_obs_searchtables_timespan_does_not_match
+t
+(1 row)
+id|description|name|aggregate|source
+us.census.acs.B01003001_quantile|The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.|Quantile:Total Population|quantile|
+es.ine.total_pop|The total number of all people living in a geographic area.|Total Population|sum|
+us.census.acs.B01003001|The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.|Total Population|sum|
+us.census.acs.B19301001|Per capita income is the mean income computed for every man, woman, and child in a particular group. It is derived by dividing the total income of a particular group by the total population.|Per Capita Income in the past 12 Months|average|
+us.census.acs.B01001001_quantile|The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.|Quantile:Total Population|quantile|
+(5 rows)
+boundary_id|description|time_span|tablename
+us.census.tiger.zcta5|ZCTAs are approximate area representations of U.S. Postal Service (USPS) five-digit ZIP Code service areas that the Census Bureau creates using whole blocks to present statistical data from censuses and surveys. The Census Bureau defines ZCTAs by allocating each block that contains addresses to a single ZCTA, usually to the ZCTA that reflects the most frequently occurring ZIP Code for the addresses within that tabulation block. Blocks that do not contain addresses but are completely surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA; those surrounded by multiple ZCTAs will be added to a single ZCTA based on limited buffering performed between multiple ZCTAs. The Census Bureau identifies five-digit ZCTAs using a five-character numeric code that represents the most frequently occurring USPS ZIP Code within that ZCTA, and this code may contain leading zeros.
+There are significant changes to the 2010 ZCTA delineation from that used in 2000. Coverage was extended to include the Island Areas for 2010 so that the United States, Puerto Rico, and the Island Areas have ZCTAs. Unlike 2000, when areas that could not be assigned to a ZCTA were given a generic code ending in “XX” (land area) or “HH” (water area), for 2010 there is no universal coverage by ZCTAs, and only legitimate five-digit areas are defined. The 2010 ZCTAs will better represent the actual Zip Code service areas because the Census Bureau initiated a process before creation of 2010 blocks to add block boundaries that split polygons with large numbers of addresses using different Zip Codes.
+Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The ZCTAs process used primarily residential addresses and was biased towards Zip Codes used for city-style mail delivery, thus there may be Zip Codes that are primarily nonresidential or boxes only that may not have a corresponding ZCTA.|2014|obs_144e8b4f906885b2e057ac4842644a553ae49c6e
+whosonfirst.wof_continent_geom|Continents of the world.|2016|obs_9880042f935aab0d0e4b71fb6963d7726e64c534
+whosonfirst.wof_country_geom| |2016|obs_1ea93bbc109c87c676b3270789dacf7a1430db6c
+whosonfirst.wof_region_geom| |2016|obs_4fca4f060854cc3ae8c109999635a71bbde6964e
+whosonfirst.wof_marinearea_geom| |2016|obs_5105018d57c69b8a7e064fc17a9485647b311a99
+whosonfirst.wof_disputed_geom| |2016|obs_7dba9374b15fbab0c7bd7dca6dec6c4792fe86a3
+us.census.tiger.congressional_district|Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states based on decennial census population counts, each state with multiple seats is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. For the District of Columbia, Puerto Rico, and each Island Area, a separate code is used to identify the entire areas of these state-equivalent entities as having a single nonvoting delegate.|2014|obs_01b608b3a4ca503ad7acc0b1f84817bc1da3e193
+us.census.tiger.congressional_district_clipped|A cartography-ready version of US Congressional Districts|2014|obs_9d258128ff4288eb9a6d7e5c0adbef8ef0172a86
+us.census.tiger.school_district_unified_clipped|A cartography-ready version of Unified School District|2014|obs_546285f2c636f5380e7bfbb0c0db67863f6ed41d
+us.census.tiger.cbsa_clipped|A cartography-ready version of Core Based Statistical Area (CBSA)|2014|obs_3512a78ca8c7e9b5fbd5390c4ed1638b9938fcbf
+us.census.tiger.block|Census blocks are statistical areas bounded by visible features, such as streets, roads, streams, and railroad tracks, and by nonvisible boundaries, such as selected property lines and city, township, school district, and county limits and short line-of-sight extensions of streets and roads. Generally, census blocks are small in area; for example, a block in a city bounded on all sides by streets. Census blocks in suburban and rural areas may be large, irregular, and bounded by a variety of features, such as roads, streams, and transmission lines. In remote areas, census blocks may encompass hundreds of square miles. Census blocks cover the entire territory of the United States, Puerto Rico, and the Island Areas. Census blocks nest within all other tabulated census geographic entities and are the basis for all tabulated data.|2014|obs_ffebc3eb689edab4faa757f75ca02c65d7db7327
+us.census.tiger.school_district_elementary_clipped|A cartography-ready version of Elementary School District|2014|obs_41d99a86857c05f63320ea44419a68831e74ac3d
+us.census.tiger.block_group_clipped|A cartography-ready version of US Census Block Groups|2014|obs_6c1309a64d8f3e6986061f4d1ca7b57743e75e74
+us.census.tiger.census_tract_clipped|A cartography-ready version of US Census Tracts|2014|obs_fcd4e4f5610f6764973ef8c0c215b2e80bec8963
+us.census.tiger.zcta5_clipped|A cartography-ready version of US Census Zip Code Tabulation Areas|2014|obs_7615e8622a68bfc5fe37c69c9880edfb40250103
+us.census.tiger.place|Incorporated places are those reported to the Census Bureau as legally in existence as of January 1, 2010, as reported in the latest Boundary and Annexation Survey (BAS), under the laws of their respective states. An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division, which generally is created to provide services or administer an area without regard, necessarily, to population. Places always are within a single state or equivalent entity, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. For Census Bureau data tabulation and presentation purposes, incorporated places exclude:
+Boroughs in Alaska (treated as statistical equivalents of counties).
+Towns in the New England states, New York, and Wisconsin (treated as MCDs).
+Boroughs in New York (treated as MCDs).
+Census Designated Places (CDPs) are the statistical counterparts of incorporated places, and are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries usually are defined in cooperation with local or tribal officials and generally updated prior to each decennial census. These boundaries, which usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity boundary, have no legal status, nor do these places have officials elected to serve traditional municipal functions. CDP boundaries may change from one decennial census
+to the next with changes in the settlement pattern; a CDP with the same name as in an earlier census does not necessarily have the same boundary. CDPs must be contained within a single state and may not extend into an incorporated place. There are no population size requirements for CDPs.
+Hawaii is the only state that has no incorporated places recognized by the Census Bureau. All places shown in decennial census data products for Hawaii are CDPs. By agreement with the state of Hawaii, the Census Bureau does not show data separately for the city of Honolulu, which is coextensive with Honolulu County. In Puerto Rico, which also does not have incorporated places, the Census Bureau recognizes only CDPs and refers to them as comunidades or zonas urbanas. Guam also has only CDPs.|2014|obs_76a52df2018de8d064f1a99f93544473927cb7ae
+us.census.tiger.place_clipped|A cartography-ready version of Incorporated Places|2014|obs_db91d46d317a4ffcf509efca8e5e3a42d29e0792
+us.census.tiger.school_district_secondary_clipped|A cartography-ready version of Secondary School District|2014|obs_63b15ba742ccea136ddb88427cc37fee218702d4
+us.census.tiger.cbsa|Core Based Statistical Areas (CBSAs) consist of the county or counties or equivalent entities associated with at least one core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties associated with the core. The general concept of a CBSA is that of a
+core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core. The term “core based statistical area” became effective in 2003 and refers collectively to metropolitan statistical areas and micropolitan statistical areas. The U.S. Office of Management and Budget (OMB) defines CBSAs to provide a nationally consistent set of geographic entities for the United States and Puerto Rico for use in tabulating and presenting statistical data. Current CBSAs are based on application of the 2000 standards (published in the Federal Register of December 27, 2000) with Census 2000 data. The first set of areas defined based on the 2000 standards were announced on June 6, 2003; subsequent updates have been made to the universe of CBSAs and related statistical areas. No CBSAs are defined in the Island Areas. Statistical areas related to CBSAs include metropolitan divisions, combined statistical areas (CSAs), New England city and town areas (NECTAs), NECTA divisions, and combined NECTAs.|2014|obs_c75be9ef45e87c789c3607dd9aeef6094d5e5109
+us.census.tiger.puma_clipped|A cartography-ready version of US Census Public Use Microdata Areas|2014|obs_dc244bf520f62e4a09e290a02e55368fd0758f95
+us.census.tiger.county|The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and census areas; the latter of which are delineated cooperatively for statistical purposes by the state of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. All of the counties in Connecticut and Rhode Island and nine counties in Massachusetts were dissolved as functioning governmental entities; however, the Census Bureau continues to present data for these historical entities in order to provide comparable geographic units at the county level of the geographic hierarchy for these states and represents them as nonfunctioning legal entities in data products. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: municipios in Puerto Rico, districts and islands in American Samoa, municipalities in the Commonwealth of the Northern Mariana Islands, and islands in the U.S. Virgin Islands. Each county or statistically equivalent entity is assigned a three-character numeric Federal Information Processing Series (FIPS) code based on alphabetical sequence that is unique within state and an eight-digit National Standard feature identifier.|2014|obs_1babf5a26a1ecda5fb74963e88408f71d0364b81
+us.census.tiger.county_clipped|A cartography-ready version of US County|2014|obs_23cb5063486bd7cf36f17e89e5e65cd31b331f6e
+us.census.tiger.school_district_unified|School Districts are geographic entities within which state, county, local officials, the Bureau of Indian Affairs, or the U.S. Department of Defense provide public educational services for the area’s residents. The Census Bureau obtains the boundaries, names, local education agency codes, and school district levels for school districts from state and local school officials for the primary purpose of providing the U.S. Department of Education with estimates of the number of children “at risk” within each school district, county, and state. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts.
+The Census Bureau tabulates data for three types of school districts: elementary, secondary, and unified. Each school district is assigned a five-digit code that is unique within state. School district codes are the local education agency number assigned by the Department of Education and are not necessarily in alphabetical order by school district name.
+The elementary school districts provide education to the lower grade/age levels and the secondary school districts provide education to the upper grade/age levels. Unified school districts provide education to children of all school ages in their service areas. In general, where there is a unified school district, no elementary or secondary school district exists; and where there is an elementary school district, the secondary school district may or may not exist.
+The Census Bureau’s representation of school districts in various data products is based both on the grade range that a school district operates and also the grade range for which the school district is financially responsible. For example, a school district is defined as an elementary school district if its operational grade range is less than the full kindergarten through 12 or prekindergarten through 12 grade range (for example, K–6 or pre-K–8). These elementary school districts do not provide direct educational services for grades 7–12, 9–12, or similar ranges. Some elementary school districts are financially responsible for the education of all school-aged children within their service areas and rely on other school districts to provide service for those grade ranges that are not operated by these elementary school districts. In these situations, in order to allocate all school-aged children to these school districts, the secondary school district code field is blank. For elementary school districts where the operational grade range and financially responsible grade range are the same, the secondary school district code field will contain a secondary school district code. There are no situations where an elementary school district does not exist and a secondary school district exists in Census Bureau records.|2014|obs_c948b5b1e4fdaf3302d888d0dc4cc821d8857c96
+us.census.tiger.census_tract|Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity that are updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program. The Census Bureau delineates census tracts in situations where no local participant existed or where state, local, or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of statistical data.
+Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however, the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census. Census tracts occasionally are split due to population growth or merged as a result of substantial population decline.
+Census tract boundaries generally follow visible and identifiable features. They may follow nonvisible legal boundaries, such as minor civil division (MCD) or incorporated place boundaries in some states and situations, to allow for census-tract-to-governmental-unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. Tribal census tracts are a unique geographic entity defined within federally recognized American Indian reservations and off-reservation trust lands and can cross state and county boundaries. Tribal census tracts may be completely different from the census tracts and block groups defined by state and county (see “Tribal Census Tract”).|2014|obs_fc050f0b8673cfe3c6aa1040f749eb40975691b7
+us.census.tiger.school_district_elementary|School Districts are geographic entities within which state, county, local officials, the Bureau of Indian Affairs, or the U.S. Department of Defense provide public educational services for the area’s residents. The Census Bureau obtains the boundaries, names, local education agency codes, and school district levels for school districts from state and local school officials for the primary purpose of providing the U.S. Department of Education with estimates of the number of children “at risk” within each school district, county, and state. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts.
+The Census Bureau tabulates data for three types of school districts: elementary, secondary, and unified. Each school district is assigned a five-digit code that is unique within state. School district codes are the local education agency number assigned by the Department of Education and are not necessarily in alphabetical order by school district name.
+The elementary school districts provide education to the lower grade/age levels and the secondary school districts provide education to the upper grade/age levels. Unified school districts provide education to children of all school ages in their service areas. In general, where there is a unified school district, no elementary or secondary school district exists; and where there is an elementary school district, the secondary school district may or may not exist.
+The Census Bureau’s representation of school districts in various data products is based both on the grade range that a school district operates and also the grade range for which the school district is financially responsible. For example, a school district is defined as an elementary school district if its operational grade range is less than the full kindergarten through 12 or prekindergarten through 12 grade range (for example, K–6 or pre-K–8). These elementary school districts do not provide direct educational services for grades 7–12, 9–12, or similar ranges. Some elementary school districts are financially responsible for the education of all school-aged children within their service areas and rely on other school districts to provide service for those grade ranges that are not operated by these elementary school districts. In these situations, in order to allocate all school-aged children to these school districts, the secondary school district code field is blank. For elementary school districts where the operational grade range and financially responsible grade range are the same, the secondary school district code field will contain a secondary school district code. There are no situations where an elementary school district does not exist and a secondary school district exists in Census Bureau records.|2014|obs_62ba00831d7f65309d6d663e2a99a688d336539a
+us.census.tiger.school_district_secondary|School Districts are geographic entities within which state, county, local officials, the Bureau of Indian Affairs, or the U.S. Department of Defense provide public educational services for the area’s residents. The Census Bureau obtains the boundaries, names, local education agency codes, and school district levels for school districts from state and local school officials for the primary purpose of providing the U.S. Department of Education with estimates of the number of children “at risk” within each school district, county, and state. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts.
+The Census Bureau tabulates data for three types of school districts: elementary, secondary, and unified. Each school district is assigned a five-digit code that is unique within state. School district codes are the local education agency number assigned by the Department of Education and are not necessarily in alphabetical order by school district name.
+The elementary school districts provide education to the lower grade/age levels and the secondary school districts provide education to the upper grade/age levels. Unified school districts provide education to children of all school ages in their service areas. In general, where there is a unified school district, no elementary or secondary school district exists; and where there is an elementary school district, the secondary school district may or may not exist.
+The Census Bureau’s representation of school districts in various data products is based both on the grade range that a school district operates and also the grade range for which the school district is financially responsible. For example, a school district is defined as an elementary school district if its operational grade range is less than the full kindergarten through 12 or prekindergarten through 12 grade range (for example, K–6 or pre-K–8). These elementary school districts do not provide direct educational services for grades 7–12, 9–12, or similar ranges. Some elementary school districts are financially responsible for the education of all school-aged children within their service areas and rely on other school districts to provide service for those grade ranges that are not operated by these elementary school districts. In these situations, in order to allocate all school-aged children to these school districts, the secondary school district code field is blank. For elementary school districts where the operational grade range and financially responsible grade range are the same, the secondary school district code field will contain a secondary school district code. There are no situations where an elementary school district does not exist and a secondary school district exists in Census Bureau records.|2014|obs_7b120df094ad943984b820d83ced7392af3a551a
+us.census.tiger.block_group|Block groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003, ..., 3999 in census tract 1210.02 belong to BG 3 in that census tract. Most BGs were delineated by local participants in the Census Bureau’s Participant Statistical Areas Program. The Census Bureau delineated BGs only where a local or tribal government declined to participate, and a regional organization or State Data Center was not available to participate.
+A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geographic hierarchy, BGs never cross state, county, or census tract boundaries but may cross the boundaries of any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries (see “Tribal Census Tract” and “Tribal Block Group”). The tribal census tracts and tribal block groups may be completely different from the census tracts and block groups defined by state and county.|2014|obs_c6fb99c47d61289fbb8e561ff7773799d3fcc308
+us.census.tiger.state|States and Equivalent Entities are the primary governmental divisions of the United States. In addition to the 50 states, the Census Bureau treats the District of Columbia, Puerto Rico, American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands as the statistical equivalents of states for the purpose of data presentation.|2014|obs_624e5d2362e08aaa5463d7671e7748432262719c
+us.census.tiger.state_clipped|A cartography-ready version of US States|2014|obs_f39f1d7cd5a22b87140860cbd58539f1591a1810
+us.census.tiger.puma|PUMAs are geographic areas for which the Census Bureau provides selected extracts of raw data from a small sample of census records that are screened to protect confidentiality. These extracts are referred to as public use microdata sample (PUMS) files.
+For the 2010 Census, each state, the District of Columbia, Puerto Rico, and some Island Area participants delineated PUMAs for use in presenting PUMS data based on a 5 percent sample of decennial census or American Community Survey data. These areas are required to contain at least 100,000 people. This is different from Census 2000 when two types of PUMAs were defined: a 5 percent PUMA as for 2010 and an additional super-PUMA designed to provide a 1 percent sample. The PUMAs are identified by a five-digit census code unique within state.|2014|obs_7c9493c41fa8f4bd178ab993ea3d5891c1977667
+(30 rows)

src/pg/test/expected/44_observatory_geometries_test.out

@@ -0,0 +1,92 @@
+\pset format unaligned
+\set ECHO all
+\i test/fixtures/load_fixtures.sql
+SET client_min_messages TO WARNING;
+\set ECHO none
+obs_getboundary_cartodb_census_tract
+t
+(1 row)
+obs_getboundary_cartodb_county
+t
+(1 row)
+obs_getboundary_non_existent_boundary_id
+t
+(1 row)
+obs_getboundary_null_island_census_tract
+t
+(1 row)
+obs_getboundary_year_census_tract
+t
+(1 row)
+obs_getboundary_unlisted_year
+t
+(1 row)
+obs_getboundaryid_cartodb_census_tract
+t
+(1 row)
+obs_getboundaryid_cartodb_census_tract_with_year
+t
+(1 row)
+obs_getboundaryid_cartodb_county_with_year
+t
+(1 row)
+obs_getboundaryid_null_island
+t
+(1 row)
+obs_getboundarybyid_cartodb_county
+t
+(1 row)
+obs_getboundarybyid_compared_with_obs_getboundary
+t
+(1 row)
+obs_getboundarybyid_boundary_id_mismatch_geom_id
+t
+(1 row)
+obs_getboundarybyid_boundary_id_mismatch_geom_id
+t
+(1 row)
+_obs_getboundariesbygeometry_tracts_around_cartodb
+t
+(1 row)
+_obs_getboundariesbygeometry_tracts_around_null_island
+t
+(1 row)
+obs_getboundariesbygeometry_tracts_around_cartodb
+t
+(1 row)
+obs_getboundariesbygeometry_tracts_around_null_island
+t
+(1 row)
+obs_getboundariesbypointandradius_around_cartodb
+t
+(1 row)
+obs_getboundariesbypointandradius_around_null_island
+t
+(1 row)
+_obs_getpointsbygeometry_around_cartodb
+t
+(1 row)
+_obs_getpointsbygeometry_around_null_island
+t
+(1 row)
+obs_getpointsbygeometry_around_cartodb
+t
+(1 row)
+obs_getpointsbygeometry_around_cartodb_2014
+t
+(1 row)
+obs_getpointsbygeometry_around_null_island
+t
+(1 row)
+obs_getpointsbypointandradius_around_cartodb
+t
+(1 row)
+obs_getpointsbypointandradius_around_cartodb_2014
+t
+(1 row)
+obs_getpointsbypointandradius_around_null_island
+t
+(1 row)
+geoid_name_matches|table_name_matches|geom_name_matches
+t|t|t
+(1 row)

src/pg/test/fixtures/drop_fixtures.sql

@@ -0,0 +1,20 @@
+SET client_min_messages TO WARNING;
+\set ECHO none
+DROP TABLE IF EXISTS observatory.obs_table;
+DROP TABLE IF EXISTS observatory.obs_column_table;
+DROP TABLE IF EXISTS observatory.obs_column;
+DROP TABLE IF EXISTS observatory.obs_column_tag;
+DROP TABLE IF EXISTS observatory.obs_tag;
+DROP TABLE IF EXISTS observatory.obs_column_to_column;
+DROP TABLE IF EXISTS observatory.obs_65f29658e096ca1485bf683f65fdbc9f05ec3c5d;
+DROP TABLE IF EXISTS observatory.obs_1746e37b7cd28cb131971ea4187d42d71f09c5f3;
+DROP TABLE IF EXISTS observatory.obs_1a098da56badf5f32e336002b0a81708c40d29cd;
+DROP TABLE IF EXISTS observatory.obs_7615e8622a68bfc5fe37c69c9880edfb40250103;
+DROP TABLE IF EXISTS observatory.obs_1babf5a26a1ecda5fb74963e88408f71d0364b81;
+DROP TABLE IF EXISTS observatory.obs_8764a6b439a4f8714f54d4b3a157bc5e36519066;
+DROP TABLE IF EXISTS observatory.obs_b393b5b88c6adda634b2071a8005b03c551b609a;
+DROP TABLE IF EXISTS observatory.obs_fc050f0b8673cfe3c6aa1040f749eb40975691b7;
+DROP TABLE IF EXISTS observatory.obs_6c1309a64d8f3e6986061f4d1ca7b57743e75e74;
+DROP TABLE IF EXISTS observatory.obs_d39f7fe5959891c8296490d83c22ded31c54af13;
+DROP TABLE IF EXISTS observatory.obs_144e8b4f906885b2e057ac4842644a553ae49c6e;
+DROP TABLE IF EXISTS observatory.obs_c6fb99c47d61289fbb8e561ff7773799d3fcc308;

src/pg/test/fixtures/obs_11ee8b82c877c073438bc935a91d3dfccef875d1.sql

@@ -1,17 +0,0 @@
-
-
-CREATE TABLE IF NOT EXISTS obs_11ee8b82c877c073438bc935a91d3dfccef875d1 (
-    cartodb_id integer,
-    the_geom geometry(Geometry,4326),
-    the_geom_webmercator geometry(Geometry,3857),
-    geoid text,
-    x10 text,
-    x2 text,
-    x31 text,
-    x55 text
-);
-
-INSERT INTO obs_11ee8b82c877c073438bc935a91d3dfccef875d1 (cartodb_id, the_geom, the_geom_webmercator, geoid, x10, x2, x31, x55) VALUES (2150, NULL, NULL, '36047048500', 'Wealthy, urban without Kids', '8', '15', '1');
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_11ee8b82c877c073438bc935a91d3dfccef875d1 SET SCHEMA observatory;

src/pg/test/fixtures/obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb.sql

@@ -1,129 +0,0 @@
-
-CREATE TABLE IF NOT EXISTS obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb (
-    cartodb_id integer,
-    the_geom geometry(Geometry,4326),
-    the_geom_webmercator geometry(Geometry,3857),
-    geoid text,
-    total_pop double precision,
-    male_pop double precision,
-    female_pop double precision,
-    median_age double precision,
-    white_pop double precision,
-    black_pop double precision,
-    asian_pop double precision,
-    hispanic_pop double precision,
-    amerindian_pop double precision,
-    other_race_pop double precision,
-    two_or_more_races_pop double precision,
-    not_hispanic_pop double precision,
-    not_us_citizen_pop double precision,
-    workers_16_and_over double precision,
-    commuters_by_car_truck_van double precision,
-    commuters_drove_alone double precision,
-    commuters_by_carpool double precision,
-    commuters_by_public_transportation double precision,
-    commuters_by_bus double precision,
-    commuters_by_subway_or_elevated double precision,
-    walked_to_work double precision,
-    worked_at_home double precision,
-    children double precision,
-    households double precision,
-    population_3_years_over double precision,
-    in_school double precision,
-    in_grades_1_to_4 double precision,
-    in_grades_5_to_8 double precision,
-    in_grades_9_to_12 double precision,
-    in_undergrad_college double precision,
-    pop_25_years_over double precision,
-    high_school_diploma double precision,
-    less_one_year_college double precision,
-    one_year_more_college double precision,
-    associates_degree double precision,
-    bachelors_degree double precision,
-    masters_degree double precision,
-    pop_5_years_over double precision,
-    speak_only_english_at_home double precision,
-    speak_spanish_at_home double precision,
-    pop_determined_poverty_status double precision,
-    poverty double precision,
-    median_income double precision,
-    gini_index double precision,
-    income_per_capita double precision,
-    housing_units double precision,
-    vacant_housing_units double precision,
-    vacant_housing_units_for_rent double precision,
-    vacant_housing_units_for_sale double precision,
-    median_rent double precision,
-    percent_income_spent_on_rent double precision,
-    owner_occupied_housing_units double precision,
-    million_dollar_housing_units double precision,
-    mortgaged_housing_units double precision,
-    families_with_young_children double precision,
-    two_parent_families_with_young_children double precision,
-    two_parents_in_labor_force_families_with_young_children double precision,
-    two_parents_father_in_labor_force_families_with_young_children double precision,
-    two_parents_mother_in_labor_force_families_with_young_children double precision,
-    two_parents_not_in_labor_force_families_with_young_children double precision,
-    one_parent_families_with_young_children double precision,
-    father_one_parent_families_with_young_children double precision,
-    men_45_to_64 double precision,
-    men_45_to_49 double precision,
-    men_50_to_54 double precision,
-    men_55_to_59 double precision,
-    men_60_61 double precision,
-    men_62_64 double precision,
-    black_men_45_54 double precision,
-    black_men_55_64 double precision,
-    hispanic_men_45_54 double precision,
-    hispanic_men_55_64 double precision,
-    white_men_45_54 double precision,
-    white_men_55_64 double precision,
-    asian_men_45_54 double precision,
-    asian_men_55_64 double precision,
-    men_45_64_less_than_9_grade double precision,
-    men_45_64_grade_9_12 double precision,
-    men_45_64_high_school double precision,
-    men_45_64_some_college double precision,
-    men_45_64_associates_degree double precision,
-    men_45_64_bachelors_degree double precision,
-    men_45_64_graduate_degree double precision,
-    father_in_labor_force_one_parent_families_with_young_children double precision,
-    pop_15_and_over double precision,
-    pop_never_married double precision,
-    pop_now_married double precision,
-    pop_separated double precision,
-    pop_widowed double precision,
-    pop_divorced double precision,
-    commuters_16_over double precision,
-    commute_less_10_mins double precision,
-    commute_10_14_mins double precision,
-    commute_15_19_mins double precision,
-    commute_20_24_mins double precision,
-    commute_25_29_mins double precision,
-    commute_30_34_mins double precision,
-    commute_35_44_mins double precision,
-    commute_45_59_mins double precision,
-    commute_60_more_mins double precision,
-    aggregate_travel_time_to_work double precision,
-    income_less_10000 double precision,
-    income_10000_14999 double precision,
-    income_15000_19999 double precision,
-    income_20000_24999 double precision,
-    income_25000_29999 double precision,
-    income_30000_34999 double precision,
-    income_35000_39999 double precision,
-    income_40000_44999 double precision,
-    income_45000_49999 double precision,
-    income_50000_59999 double precision,
-    income_60000_74999 double precision,
-    income_75000_99999 double precision,
-    income_100000_124999 double precision,
-    income_125000_149999 double precision,
-    income_150000_199999 double precision,
-    income_200000_or_more double precision
-);
-
-INSERT INTO obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb (cartodb_id, the_geom, the_geom_webmercator, geoid, total_pop, male_pop, female_pop, median_age, white_pop, black_pop, asian_pop, hispanic_pop, amerindian_pop, other_race_pop, two_or_more_races_pop, not_hispanic_pop, not_us_citizen_pop, workers_16_and_over, commuters_by_car_truck_van, commuters_drove_alone, commuters_by_carpool, commuters_by_public_transportation, commuters_by_bus, commuters_by_subway_or_elevated, walked_to_work, worked_at_home, children, households, population_3_years_over, in_school, in_grades_1_to_4, in_grades_5_to_8, in_grades_9_to_12, in_undergrad_college, pop_25_years_over, high_school_diploma, less_one_year_college, one_year_more_college, associates_degree, bachelors_degree, masters_degree, pop_5_years_over, speak_only_english_at_home, speak_spanish_at_home, pop_determined_poverty_status, poverty, median_income, gini_index, income_per_capita, housing_units, vacant_housing_units, vacant_housing_units_for_rent, vacant_housing_units_for_sale, median_rent, percent_income_spent_on_rent, owner_occupied_housing_units, million_dollar_housing_units, mortgaged_housing_units, families_with_young_children, two_parent_families_with_young_children, two_parents_in_labor_force_families_with_young_children, two_parents_father_in_labor_force_families_with_young_children, two_parents_mother_in_labor_force_families_with_young_children, two_parents_not_in_labor_force_families_with_young_children, one_parent_families_with_young_children, father_one_parent_families_with_young_children, men_45_to_64, men_45_to_49, men_50_to_54, men_55_to_59, men_60_61, men_62_64, black_men_45_54, black_men_55_64, hispanic_men_45_54, hispanic_men_55_64, white_men_45_54, white_men_55_64, asian_men_45_54, asian_men_55_64, men_45_64_less_than_9_grade, men_45_64_grade_9_12, men_45_64_high_school, men_45_64_some_college, men_45_64_associates_degree, men_45_64_bachelors_degree, men_45_64_graduate_degree, father_in_labor_force_one_parent_families_with_young_children, pop_15_and_over, pop_never_married, pop_now_married, pop_separated, pop_widowed, pop_divorced, commuters_16_over, commute_less_10_mins, commute_10_14_mins, commute_15_19_mins, commute_20_24_mins, commute_25_29_mins, commute_30_34_mins, commute_35_44_mins, commute_45_59_mins, commute_60_more_mins, aggregate_travel_time_to_work, income_less_10000, income_10000_14999, income_15000_19999, income_20000_24999, income_25000_29999, income_30000_34999, income_35000_39999, income_40000_44999, income_45000_49999, income_50000_59999, income_60000_74999, income_75000_99999, income_100000_124999, income_125000_149999, income_150000_199999, income_200000_or_more) VALUES (132625, NULL, NULL, '360470485002', 1655, 1070, 585, 28.8000000000000007, 922, 26, 40, 667, 0, 0, 0, 988, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 578, NULL, NULL, NULL, NULL, NULL, NULL, 1236, 181, 12, 138, 57, 477, 162, NULL, NULL, NULL, NULL, NULL, 66304, 0.349399999999999988, 28291, 637, 59, 21, 0, 1764, 35.2999999999999972, 59, 0, 39, 60, 47, 22, 25, 0, 0, 13, 0, NULL, 12, 64, 6, 15, 0, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 0, NULL, NULL, NULL, NULL, NULL, NULL, 1139, 57, 5, 35, 108, 65, 322, 246, 194, 107, NULL, 10, 0, 37, 71, 0, 27, 19, 16, 11, 32, 108, 96, 57, 58, 22, 14);
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb SET SCHEMA observatory;

src/pg/test/fixtures/obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1.sql

@@ -1,12 +0,0 @@
-
-CREATE TABLE IF NOT EXISTS obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1 (
-    cartodb_id integer,
-    the_geom geometry(Geometry,4326),
-    the_geom_webmercator geometry(Geometry,3857),
-    geoid text
-);
-
-INSERT INTO obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1(cartodb_id, the_geom, the_geom_webmercator, geoid) VALUES (129734, '0106000020E6100000010000000103000000010000001B000000373465A71F7C52C065A71FD4455A4440AE105663097C52C0016729594E5A4440CFD90242EB7B52C07EA5F3E1595A4440F98381E7DE7B52C0E1CE85915E5A44407A6F0C01C07B52C0E1EB6B5D6A5A44401B9B1DA9BE7B52C03F6F2A52615A444088855AD3BC7B52C088669E5C535A4440E1EA0088BB7B52C0E6E95C514A5A44400CE6AF90B97B52C070D05E7D3C5A44401E85EB51B87B52C0B03A72A4335A4440BAF3C473B67B52C09929ADBF255A4440CD920035B57B52C0454AB3791C5A4440F78DAF3DB37B52C0E09BA6CF0E5A4440DBC2F352B17B52C0703FE081015A444015C440D7BE7B52C05E83BEF4F659444041446ADAC57B52C0EFDFBC38F15944405FB1868BDC7B52C0C03E3A75E559444034BC5983F77B52C0205ED72FD8594440EFFCA204FD7B52C07E384888F25944403ACAC16C027C52C00876FC17085A444056478E74067C52C00FECF82F105A44400FECF82F107C52C0876D8B321B5A4440BB438A01127C52C0DE1CAED51E5A4440B9C15087157C52C034643C4A255A444099F221A81A7C52C0D0EFFB372F5A44404AED45B41D7C52C0785DBF60375A4440373465A71F7C52C065A71FD4455A4440', '0106000020110F0000010000000103000000010000001B00000032BDDDFAFC655FC153A8E8ED80F45241B0FCBD28D7655FC14F4D6A798AF452412123E2FAA3655FC162ED8F6597F45241D9CC0CFF8E655FC1B67D80A59CF45241619957825A655FC1AB01DCDCA9F45241F732233A58655FC1E64AF3BA9FF45241FD0A331C55655FC1BF49541790F45241EE375EE952655FC1CF9272F585F45241AA316F924F655FC1D4F7757776F45241F8F1F9744D655FC1408CFE8D6CF452416B12CA484A655FC156BE40FD5CF45241B8D2542B48655FC149DCA39952F4524175CC65D444655FC106D3B94A43F452418E59D69241655FC1C23D366334F452419AA4818858655FC16C90219128F45241CD18C57164655FC1A533872422F45241BD2B21FD8A655FC1F390C1F614F45241B152F8CBB8655FC14A47B61806F452419ECAC825C2655FC16FDF6F9C23F45241D71BDA54CB655FC11F9B2BC43BF45241144F772DD2655FC116806FD544F45241AB4763B5E2655FC1CE331F2B51F45241DD9333CCE5655FC196244A3E55F45241BF29F5C7EB655FC1FB82AE795CF452419DE2E87DF4655FC145D3439967F45241B8920EABF9655FC1DB285EBD70F4524132BDDDFAFC655FC153A8E8ED80F45241', '360470485002');
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1 SET SCHEMA observatory;

src/pg/test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql

@@ -1,12 +0,0 @@
-
-CREATE TABLE IF NOT EXISTS obs_a92e1111ad3177676471d66bb8036e6d057f271b (
-    cartodb_id integer,
-    the_geom geometry(Geometry,4326),
-    the_geom_webmercator geometry(Geometry,3857),
-    geoid text
-);
-
-INSERT INTO obs_a92e1111ad3177676471d66bb8036e6d057f271b (cartodb_id, the_geom, the_geom_webmercator, geoid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
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_a92e1111ad3177676471d66bb8036e6d057f271b SET SCHEMA observatory;

src/pg/test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql

@@ -1,129 +0,0 @@
-
-CREATE TABLE IF NOT EXISTS obs_ab038198aaab3f3cb055758638ee4de28ad70146 (
-    cartodb_id integer,
-    the_geom geometry(Geometry,4326),
-    the_geom_webmercator geometry(Geometry,3857),
-    geoid text,
-    total_pop double precision,
-    male_pop double precision,
-    female_pop double precision,
-    median_age double precision,
-    white_pop double precision,
-    black_pop double precision,
-    asian_pop double precision,
-    hispanic_pop double precision,
-    amerindian_pop double precision,
-    other_race_pop double precision,
-    two_or_more_races_pop double precision,
-    not_hispanic_pop double precision,
-    not_us_citizen_pop double precision,
-    workers_16_and_over double precision,
-    commuters_by_car_truck_van double precision,
-    commuters_drove_alone double precision,
-    commuters_by_carpool double precision,
-    commuters_by_public_transportation double precision,
-    commuters_by_bus double precision,
-    commuters_by_subway_or_elevated double precision,
-    walked_to_work double precision,
-    worked_at_home double precision,
-    children double precision,
-    households double precision,
-    population_3_years_over double precision,
-    in_school double precision,
-    in_grades_1_to_4 double precision,
-    in_grades_5_to_8 double precision,
-    in_grades_9_to_12 double precision,
-    in_undergrad_college double precision,
-    pop_25_years_over double precision,
-    high_school_diploma double precision,
-    less_one_year_college double precision,
-    one_year_more_college double precision,
-    associates_degree double precision,
-    bachelors_degree double precision,
-    masters_degree double precision,
-    pop_5_years_over double precision,
-    speak_only_english_at_home double precision,
-    speak_spanish_at_home double precision,
-    pop_determined_poverty_status double precision,
-    poverty double precision,
-    median_income double precision,
-    gini_index double precision,
-    income_per_capita double precision,
-    housing_units double precision,
-    vacant_housing_units double precision,
-    vacant_housing_units_for_rent double precision,
-    vacant_housing_units_for_sale double precision,
-    median_rent double precision,
-    percent_income_spent_on_rent double precision,
-    owner_occupied_housing_units double precision,
-    million_dollar_housing_units double precision,
-    mortgaged_housing_units double precision,
-    families_with_young_children double precision,
-    two_parent_families_with_young_children double precision,
-    two_parents_in_labor_force_families_with_young_children double precision,
-    two_parents_father_in_labor_force_families_with_young_children double precision,
-    two_parents_mother_in_labor_force_families_with_young_children double precision,
-    two_parents_not_in_labor_force_families_with_young_children double precision,
-    one_parent_families_with_young_children double precision,
-    father_one_parent_families_with_young_children double precision,
-    men_45_to_64 double precision,
-    men_45_to_49 double precision,
-    men_50_to_54 double precision,
-    men_55_to_59 double precision,
-    men_60_61 double precision,
-    men_62_64 double precision,
-    black_men_45_54 double precision,
-    black_men_55_64 double precision,
-    hispanic_men_45_54 double precision,
-    hispanic_men_55_64 double precision,
-    white_men_45_54 double precision,
-    white_men_55_64 double precision,
-    asian_men_45_54 double precision,
-    asian_men_55_64 double precision,
-    men_45_64_less_than_9_grade double precision,
-    men_45_64_grade_9_12 double precision,
-    men_45_64_high_school double precision,
-    men_45_64_some_college double precision,
-    men_45_64_associates_degree double precision,
-    men_45_64_bachelors_degree double precision,
-    men_45_64_graduate_degree double precision,
-    father_in_labor_force_one_parent_families_with_young_children double precision,
-    pop_15_and_over double precision,
-    pop_never_married double precision,
-    pop_now_married double precision,
-    pop_separated double precision,
-    pop_widowed double precision,
-    pop_divorced double precision,
-    commuters_16_over double precision,
-    commute_less_10_mins double precision,
-    commute_10_14_mins double precision,
-    commute_15_19_mins double precision,
-    commute_20_24_mins double precision,
-    commute_25_29_mins double precision,
-    commute_30_34_mins double precision,
-    commute_35_44_mins double precision,
-    commute_45_59_mins double precision,
-    commute_60_more_mins double precision,
-    aggregate_travel_time_to_work double precision,
-    income_less_10000 double precision,
-    income_10000_14999 double precision,
-    income_15000_19999 double precision,
-    income_20000_24999 double precision,
-    income_25000_29999 double precision,
-    income_30000_34999 double precision,
-    income_35000_39999 double precision,
-    income_40000_44999 double precision,
-    income_45000_49999 double precision,
-    income_50000_59999 double precision,
-    income_60000_74999 double precision,
-    income_75000_99999 double precision,
-    income_100000_124999 double precision,
-    income_125000_149999 double precision,
-    income_150000_199999 double precision,
-    income_200000_or_more double precision
-);
-
-INSERT INTO obs_ab038198aaab3f3cb055758638ee4de28ad70146 (cartodb_id, the_geom, the_geom_webmercator, geoid, total_pop, male_pop, female_pop, median_age, white_pop, black_pop, asian_pop, hispanic_pop, amerindian_pop, other_race_pop, two_or_more_races_pop, not_hispanic_pop, not_us_citizen_pop, workers_16_and_over, commuters_by_car_truck_van, commuters_drove_alone, commuters_by_carpool, commuters_by_public_transportation, commuters_by_bus, commuters_by_subway_or_elevated, walked_to_work, worked_at_home, children, households, population_3_years_over, in_school, in_grades_1_to_4, in_grades_5_to_8, in_grades_9_to_12, in_undergrad_college, pop_25_years_over, high_school_diploma, less_one_year_college, one_year_more_college, associates_degree, bachelors_degree, masters_degree, pop_5_years_over, speak_only_english_at_home, speak_spanish_at_home, pop_determined_poverty_status, poverty, median_income, gini_index, income_per_capita, housing_units, vacant_housing_units, vacant_housing_units_for_rent, vacant_housing_units_for_sale, median_rent, percent_income_spent_on_rent, owner_occupied_housing_units, million_dollar_housing_units, mortgaged_housing_units, families_with_young_children, two_parent_families_with_young_children, two_parents_in_labor_force_families_with_young_children, two_parents_father_in_labor_force_families_with_young_children, two_parents_mother_in_labor_force_families_with_young_children, two_parents_not_in_labor_force_families_with_young_children, one_parent_families_with_young_children, father_one_parent_families_with_young_children, men_45_to_64, men_45_to_49, men_50_to_54, men_55_to_59, men_60_61, men_62_64, black_men_45_54, black_men_55_64, hispanic_men_45_54, hispanic_men_55_64, white_men_45_54, white_men_55_64, asian_men_45_54, asian_men_55_64, men_45_64_less_than_9_grade, men_45_64_grade_9_12, men_45_64_high_school, men_45_64_some_college, men_45_64_associates_degree, men_45_64_bachelors_degree, men_45_64_graduate_degree, father_in_labor_force_one_parent_families_with_young_children, pop_15_and_over, pop_never_married, pop_now_married, pop_separated, pop_widowed, pop_divorced, commuters_16_over, commute_less_10_mins, commute_10_14_mins, commute_15_19_mins, commute_20_24_mins, commute_25_29_mins, commute_30_34_mins, commute_35_44_mins, commute_45_59_mins, commute_60_more_mins, aggregate_travel_time_to_work, income_less_10000, income_10000_14999, income_15000_19999, income_20000_24999, income_25000_29999, income_30000_34999, income_35000_39999, income_40000_44999, income_45000_49999, income_50000_59999, income_60000_74999, income_75000_99999, income_100000_124999, income_125000_149999, income_150000_199999, income_200000_or_more) VALUES (44715, NULL, NULL, '36047048500', 2794, 1793, 1001, 28, 1528, 80, 100, 1066, 0, 14, 6, 1728, 316, 1996, 117, 101, 16, 1453, 46, 1394, 145, 81, 174, 897, 2728, 554, 20, 13, 35, 182, 2064, 335, 19, 197, 109, 801, 299, 2715, 1696, 839, 2794, 564, 73170, 0.38919999999999999, 29516, 1009, 112, 21, 0, 1733, 29.3999999999999986, 106, 0, 74, 91, 61, 22, 25, 0, 14, 30, 17, 150, 31, 67, 6, 15, 31, 0, 0, 37, 52, 61, 0, 0, 0, 18, 6, 53, 6, 16, 23, 28, 17, 2627, 2035, 393, 65, 35, 19, 1915, 82, 24, 77, 172, 169, 461, 457, 297, 176, 67175, 10, 11, 37, 96, 29, 52, 19, 24, 11, 57, 123, 151, 68, 94, 45, 70);
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_ab038198aaab3f3cb055758638ee4de28ad70146 SET SCHEMA observatory;

src/pg/test/fixtures/obs_column.sql

@@ -1,841 +0,0 @@
-
-CREATE TABLE obs_column (cartodb_id bigint, the_geom geometry, the_geom_webmercator geometry, id text, type text, name text, description text, weight numeric, aggregate text, version text, extra json);
-
-
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (590, NULL, NULL, '"us.census.tiger".geom', 'Geometry', NULL, NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (628, NULL, NULL, '"us.census.acs".B15001027', 'Numeric', 'Men age 45 to 64 ("middle aged")', '0', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (661, NULL, NULL, '"us.ny.nyc.opendata".document_id', 'Text', 'Document ID', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (752, NULL, NULL, '"us.census.acs".B25075001_quantile', 'Numeric', 'Quantile:Owner-occupied Housing Units', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (1, NULL, NULL, '"es.ine".gender', 'Text', 'Gender', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (2, NULL, NULL, '"es.ine".total_pop', 'Numeric', 'Total Population', 'The total number of all people living in a geographic area.', 10, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (3, NULL, NULL, '"es.ine".pop_100_more', 'Numeric', 'Population age 100 or more', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (4, NULL, NULL, '"es.ine".pop_0_4', 'Numeric', 'Population age 0 to 4', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (5, NULL, NULL, '"es.ine".pop_5_9', 'Numeric', 'Population age 5 to 9', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (6, NULL, NULL, '"es.ine".pop_10_14', 'Numeric', 'Population age 10 to 14', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (7, NULL, NULL, '"es.ine".pop_15_19', 'Numeric', 'Population age 15 to 19', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (8, NULL, NULL, '"es.ine".pop_20_24', 'Numeric', 'Population age 20 to 24', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (9, NULL, NULL, '"es.ine".pop_25_29', 'Numeric', 'Population age 25 to 29', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (10, NULL, NULL, '"es.ine".pop_30_34', 'Numeric', 'Population age 30 to 34', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (11, NULL, NULL, '"es.ine".pop_35_39', 'Numeric', 'Population age 35 to 39', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (12, NULL, NULL, '"es.ine".pop_40_44', 'Numeric', 'Population age 40 to 44', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (13, NULL, NULL, '"es.ine".pop_45_49', 'Numeric', 'Population age 45 to 49', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (14, NULL, NULL, '"es.ine".pop_50_54', 'Numeric', 'Population age 50 to 54', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (15, NULL, NULL, '"es.ine".pop_55_59', 'Numeric', 'Population age 55 to 59', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (16, NULL, NULL, '"es.ine".pop_60_64', 'Numeric', 'Population age 60 to 64', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (17, NULL, NULL, '"es.ine".pop_65_69', 'Numeric', 'Population age 65 to 69', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (18, NULL, NULL, '"es.ine".pop_70_74', 'Numeric', 'Population age 70 to 74', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (19, NULL, NULL, '"es.ine".pop_75_79', 'Numeric', 'Population age 75 to 79', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (20, NULL, NULL, '"es.ine".pop_80_84', 'Numeric', 'Population age 80 to 84', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (21, NULL, NULL, '"es.ine".pop_85_89', 'Numeric', 'Population age 85 to 89', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (22, NULL, NULL, '"es.ine".pop_90_94', 'Numeric', 'Population age 90 to 94', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (23, NULL, NULL, '"es.ine".pop_95_99', 'Numeric', 'Population age 95 to 99', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (24, NULL, NULL, '"us.census.lodes".total_jobs', 'Integer', 'Total Jobs', 'Total number of jobs', 8, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (25, NULL, NULL, '"us.census.lodes".jobs_firm_age_500_more_employees', 'Integer', 'Jobs at firms with 500  Employees', 'Number of jobs for workers at firms with Firm Size: 500  Employees', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (26, NULL, NULL, '"us.census.lodes".jobs_age_29_or_younger', 'Integer', 'Jobs for workers age 29 or younger', 'Number of jobs of workers age 29 or younger', 3, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (27, NULL, NULL, '"us.census.lodes".jobs_age_30_to_54', 'Integer', 'Jobs for workers age 30 to 54', 'Number of jobs for workers age 30 to 54', 3, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (28, NULL, NULL, '"us.census.lodes".jobs_age_55_or_older', 'Integer', 'Jobs for workers age 55 or older', 'Number of jobs for workers age 55 or older', 3, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (29, NULL, NULL, '"us.census.lodes".jobs_earning_15000_or_less', 'Integer', 'Jobs earning up to $15,000 per year', 'Number of jobs with earnings $1250/month or less ($15,000 per year)', 3, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (30, NULL, NULL, '"us.census.lodes".jobs_earning_15001_to_40000', 'Integer', 'Jobs earning $15,000 to $40,000 per year', 'Number of jobs with earnings $1251/month to $3333/month ($15,000 to $40,000 per year)', 5, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (31, NULL, NULL, '"us.census.lodes".jobs_earning_40001_or_more', 'Integer', 'Jobs with earnings greater than $40,000 per year', 'Number of Jobs with earnings greater than $3333/month', 5, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (32, NULL, NULL, '"us.census.lodes".jobs_11_agriculture_forestry_fishing', 'Integer', 'Agriculture, Forestry, Fishing and Hunting jobs', 'Number of jobs in NAICS sector 11 (Agriculture, Forestry, Fishing and Hunting)', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (33, NULL, NULL, '"us.census.lodes".jobs_21_mining_quarrying_oil_gas', 'Integer', 'Mining, Quarrying, and Oil and Gas Extraction jobs', 'Number of jobs in NAICS sector 21 (Mining, Quarrying, and Oil and Gas Extraction) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (34, NULL, NULL, '"us.census.lodes".jobs_22_utilities', 'Integer', 'Utilities Jobs', 'Number of jobs in NAICS sector 22 (Utilities) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (35, NULL, NULL, '"us.census.lodes".jobs_23_construction', 'Integer', 'Construction Jobs', 'Number of jobs in NAICS sector 23 (Construction) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (36, NULL, NULL, '"us.census.lodes".jobs_31_33_manufacturing', 'Integer', 'Manufacturing Jobs', 'Number of jobs in NAICS sector 31-33 (Manufacturing) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (37, NULL, NULL, '"us.census.lodes".jobs_42_wholesale_trade', 'Integer', 'Wholesale Trade Jobs', 'Number of jobs in NAICS sector 42 (Wholesale Trade) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (38, NULL, NULL, '"us.census.lodes".jobs_44_45_retail_trade', 'Integer', 'Retail Trade Jobs', 'Number of jobs in NAICS sector 44-45 (Retail Trade) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (39, NULL, NULL, '"us.census.lodes".jobs_48_49_transport_warehousing', 'Integer', 'Transport and Warehousing Jobs', 'Number of jobs in NAICS sector 48-49 (Transportation and Warehousing) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (40, NULL, NULL, '"us.census.lodes".jobs_51_information', 'Integer', 'Information Jobs', 'Number of jobs in NAICS sector 51 (Information) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (41, NULL, NULL, '"us.census.lodes".jobs_52_finance_and_insurance', 'Integer', 'Finance and Insurance Jobs', 'Number of jobs in NAICS sector 52 (Finance and Insurance)', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (42, NULL, NULL, '"us.census.lodes".jobs_53_real_estate_rental_leasing', 'Integer', 'Real Estate and Rental and Leasing Jobs', 'Number of jobs in NAICS sector 53 (Real Estate and Rental and Leasing) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (43, NULL, NULL, '"us.census.lodes".jobs_54_professional_scientific_tech_services', 'Integer', 'Professional, Scientific, and Technical Services Jobs', 'Number of jobs in NAICS sector 54 (Professional, Scientific, and Technical Services) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (44, NULL, NULL, '"us.census.lodes".jobs_55_management_of_companies_enterprises', 'Integer', 'Management of Companies and Enterprises Jobs', 'Number of jobs in NAICS sector 55 (Management of Companies and Enterprises) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (45, NULL, NULL, '"us.census.lodes".jobs_56_admin_support_waste_management', 'Integer', 'Administrative and Support and Waste Management and Remediation Services Jobs', 'Number of jobs in NAICS sector 56 (Administrative and Support and Waste Management and Remediation Services) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (46, NULL, NULL, '"us.census.lodes".jobs_61_educational_services', 'Integer', 'Educational Services Jobs', 'Number of jobs in NAICS sector 61 (Educational Services) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (47, NULL, NULL, '"us.census.lodes".jobs_62_healthcare_social_assistance', 'Integer', 'Health Care and Social Assistance Jobs', 'Number of jobs in NAICS sector 62 (Health Care and Social Assistance) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (48, NULL, NULL, '"us.census.lodes".jobs_71_arts_entertainment_recreation', 'Integer', 'Arts, Entertainment, and Recreation jobs', 'Number of jobs in NAICS sector 71 (Arts, Entertainment, and Recreation) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (49, NULL, NULL, '"us.census.lodes".jobs_72_accommodation_and_food', 'Integer', 'Accommodation and Food Services jobs', 'Number of jobs in NAICS sector 72 (Accommodation and Food Services) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (119, NULL, NULL, '"us.census.acs".B01001015', 'Numeric', 'Men age 45 to 49', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (50, NULL, NULL, '"us.census.lodes".jobs_81_other_services_except_public_admin', 'Integer', 'Other Services (except Public Administration) jobs', 'Jobs in NAICS sector 81 (Other Services [except Public Administration])', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (51, NULL, NULL, '"us.census.lodes".jobs_92_public_administration', 'Integer', 'Public Administration jobs', 'Number of jobs in NAICS sector 92 (Public Administration) ', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (52, NULL, NULL, '"us.census.lodes".jobs_white', 'Integer', 'Jobs held by workers who are white', 'Number of jobs for workers with Race: White, Alone', 2, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (53, NULL, NULL, '"us.census.lodes".jobs_black', 'Integer', 'Jobs held by workers who are black', 'Number of jobs for workers with Race: Black or African American Alone', 2, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (54, NULL, NULL, '"us.bls".industry_code', 'Text', 'Six-digit NAICS Industry Code', '6-character Industry Code (NAICS SuperSector)', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (55, NULL, NULL, '"us.census.tiger".county', 'Geometry', 'US County', 'The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and census areas; the latter of which are delineated cooperatively for statistical purposes by the state of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. All of the counties in Connecticut and Rhode Island and nine counties in Massachusetts were dissolved as functioning governmental entities; however, the Census Bureau continues to present data for these historical entities in order to provide comparable geographic units at the county level of the geographic hierarchy for these states and represents them as nonfunctioning legal entities in data products. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: municipios in Puerto Rico, districts and islands in American Samoa, municipalities in the Commonwealth of the Northern Mariana Islands, and islands in the U.S. Virgin Islands. Each county or statistically equivalent entity is assigned a three-character numeric Federal Information Processing Series (FIPS) code based on alphabetical sequence that is unique within state and an eight-digit National Standard feature identifier.', 7, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (56, NULL, NULL, '"us.census.tiger".state', 'Geometry', 'US States', 'States and Equivalent Entities are the primary governmental divisions of the United States. In addition to the 50 states, the Census Bureau treats the District of Columbia, Puerto Rico, American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands as the statistical equivalents of states for the purpose of data presentation.', 8, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (57, NULL, NULL, '"us.census.tiger".puma', 'Geometry', 'US Census Public Use Microdata Areas', 'PUMAs are geographic areas for which the Census Bureau provides selected extracts of raw data from a small sample of census records that are screened to protect confidentiality. These extracts are referred to as public use microdata sample (PUMS) files.
-
-For the 2010 Census, each state, the District of Columbia, Puerto Rico, and some Island Area participants delineated PUMAs for use in presenting PUMS data based on a 5 percent sample of decennial census or American Community Survey data. These areas are required to contain at least 100,000 people. This is different from Census 2000 when two types of PUMAs were defined: a 5 percent PUMA as for 2010 and an additional super-PUMA designed to provide a 1 percent sample. The PUMAs are identified by a five-digit census code unique within state.', 6, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (58, NULL, NULL, '"us.census.tiger".block_group', 'Geometry', 'US Census Block Groups', 'Block groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003, ..., 3999 in census tract 1210.02 belong to BG 3 in that census tract. Most BGs were delineated by local participants in the Census Bureau\u2019s Participant Statistical Areas Program. The Census Bureau delineated BGs only where a local or tribal government declined to participate, and a regional organization or State Data Center was not available to participate.
-
-A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geographic hierarchy, BGs never cross state, county, or census tract boundaries but may cross the boundaries of any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries (see \u201cTribal Census Tract\u201d and \u201cTribal Block Group\u201d). The tribal census tracts and tribal block groups may be completely different from the census tracts and block groups defined by state and county.', 10, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (59, NULL, NULL, '"us.census.tiger".census_tract', 'Geometry', 'US Census Tracts', 'Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.
-
-Some ranges of census tract numbers in the 2010 Census are used to identify distinctive types of census tracts. The code range in the 9400s is used for those census tracts with a majority of population, housing, or land area associated with an American Indian area and matches the numbering used in Census 2000. The code range in the 9800s is new for 2010 and is used to specifically identify special land-use census tracts; that is, census tracts defined to encompass a large area with little or no residential population with special characteristics, such as large parks or employment areas. The range of census tracts in the 9900s represents census tracts delineated specifically to cover large bodies of water. This is different from Census 2000 when water-only census tracts were assigned codes of all zeroes (000000); 000000 is no longer used as a census tract code for the 2010 Census.
-
-The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Census tract suffixes may range from .01 to .98. As part of local review of existing census tracts before each census, some census tracts may have grown enough in population size to qualify as more than one census tract. When a census tract is split, the split parts usually retain the basic number but receive different suffixes. For example, if census tract 14 is split, the new tract numbers would be 14.01 and 14.02. In a few counties, local participants request major changes to, and renumbering of, the census tracts; however, this is generally discouraged. Changes to individual census tract boundaries usually do not result in census tract numbering changes.
-
-The Census Bureau introduced the concept of tribal census tracts for the first time for Census 2000. Tribal census tracts for that census consisted of the standard county-based census tracts tabulated within American Indian areas, thus allowing for the tracts to ignore state and county boundaries for tabulation. The Census Bureau assigned the 9400 range of numbers to identify specific tribal census tracts; however, not all tribal census tracts used this numbering scheme. For the 2010 Census, tribal census tracts no longer are tied to or numbered in the same way as the county-based census tracts (see \u201cTribal Census Tract\u201d).', 9, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (60, NULL, NULL, '"us.census.tiger".congressional_district', 'Geometry', 'US Congressional Districts', 'Congressional districts are identified by a two-character numeric Federal Information Processing Series (FIPS) code numbered uniquely within the state. The District of Columbia, Puerto Rico, and the Island Areas have code 98 assigned identifying their nonvoting delegate status with respect to representation in Congress:
-
-01 to 53: Congressional district codes
-00: At large (single district for state)
-98: Nonvoting delegate', 5, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (61, NULL, NULL, '"us.census.lodes".jobs_amerindian', 'Integer', 'Jobs held by workers who are American Indian or Alaska Native Alone', 'Number of jobs for workers with Race: American Indian or Alaska Native Alone', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (62, NULL, NULL, '"us.census.lodes".jobs_asian', 'Integer', 'Jobs held by workers who are Asian', 'Number of jobs for workers with Race: Asian Alone', 2, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (63, NULL, NULL, '"us.census.lodes".jobs_hawaiian', 'Integer', 'Jobs held by workers who are Native Hawaiian or Other Pacific Islander Alone', 'Number of jobs for workers with Race: Native Hawaiian or Other Pacific Islander Alone', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (64, NULL, NULL, '"us.census.lodes".jobs_two_or_more_races', 'Integer', 'Jobs held by workers who reported Two or More Race Groups', 'Number of jobs for workers with Race: Two or More Race Groups', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (128, NULL, NULL, '"us.census.acs".B01001H012', 'Numeric', 'White Men age 45 to 54', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (65, NULL, NULL, '"us.census.lodes".jobs_not_hispanic', 'Integer', 'Jobs held by workers who are Not Hispanic or Latino', 'Number of jobs for workers with Ethnicity: Not Hispanic or Latino', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (66, NULL, NULL, '"us.census.acs".B01001001', 'Numeric', 'Total Population', 'The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.', 10, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (67, NULL, NULL, '"us.census.acs".B15001034', 'Numeric', 'Men age 45 to 64 who obtained a graduate or professional degree', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (68, NULL, NULL, '"us.census.acs".B01001002', 'Numeric', 'Male Population', 'The number of people within each geography who are male.', 8, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (69, NULL, NULL, '"us.census.acs".B01001026', 'Numeric', 'Female Population', 'The number of people within each geography who are female.', 8, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (70, NULL, NULL, '"us.census.acs".B01002001', 'Numeric', 'Median Age', 'The median age of all people in a given geographic area.', 2, 'median', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (71, NULL, NULL, '"us.census.acs".B03002003', 'Numeric', 'White Population', 'The number of people identifying as white, non-Hispanic in each geography.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (72, NULL, NULL, '"us.census.acs".B03002004', 'Numeric', 'Black or African American Population', 'The number of people identifying as black or African American, non-Hispanic in each geography.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (73, NULL, NULL, '"us.census.acs".B03002006', 'Numeric', 'Asian Population', 'The number of people identifying as Asian, non-Hispanic in each geography.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (74, NULL, NULL, '"us.census.acs".B03002012', 'Numeric', 'Hispanic Population', 'The number of people identifying as Hispanic or Latino in each geography.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (75, NULL, NULL, '"us.census.acs".B05001006', 'Numeric', 'Not a U.S. Citizen Population', 'The number of people within each geography who indicated that they are not U.S. citizens.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (76, NULL, NULL, '"us.census.acs".B08006017', 'Numeric', 'Worked at Home', 'The count within a geographical area of workers over the age of 16 who worked at home.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (77, NULL, NULL, '"us.census.acs".B08006008', 'Numeric', 'Commuters by Public Transportation', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by public transportation.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (78, NULL, NULL, '"us.census.acs".B08006015', 'Numeric', 'Walked to Work', 'The number of workers age 16 years and over within a geographic area who primarily walked to work.  This would mean that of any way of getting to work, they travelled the most distance walking.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (79, NULL, NULL, '"us.census.acs".B08006009', 'Numeric', 'Commuters by Bus', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by bus.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (80, NULL, NULL, '"us.census.acs".B08006011', 'Numeric', 'Commuters by Subway or Elevated', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by subway or elevated train.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (81, NULL, NULL, '"us.census.acs".B09001001', 'Numeric', 'children under 18 Years of Age', 'The number of people within each geography who are under 18 years of age.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (82, NULL, NULL, '"us.census.acs".B14001001', 'Numeric', 'Population 3 Years and Over', 'The total number of people in each geography age 3 years and over.  This denominator is mostly used to calculate rates of school enrollment.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (83, NULL, NULL, '"us.census.acs".B14001002', 'Numeric', 'Students Enrolled in School', 'The total number of people in each geography currently enrolled at any level of school, from nursery or pre-school to advanced post-graduate education.  Only includes those over the age of 3.', 6, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (84, NULL, NULL, '"us.census.acs".B14001008', 'Numeric', 'Students Enrolled as Undergraduate in College', 'The number of people in a geographic area who are enrolled in college at the undergraduate level. Enrollment refers to being registered or listed as a student in an educational program leading to a college degree. This may be a public school or college, a private school or college.', 5, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (85, NULL, NULL, '"us.census.acs".B14001005', 'Numeric', 'Students Enrolled in Grades 1 to 4', 'The total number of people in each geography currently enrolled in grades 1 through 4 inclusive.  This corresponds roughly to elementary school.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (86, NULL, NULL, '"us.census.acs".B14001006', 'Numeric', 'Students Enrolled in Grades 5 to 8', 'The total number of people in each geography currently enrolled in grades 5 through 8 inclusive.  This corresponds roughly to middle school.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (87, NULL, NULL, '"us.census.acs".B14001007', 'Numeric', 'Students Enrolled in Grades 9 to 12', 'The total number of people in each geography currently enrolled in grades 9 through 12 inclusive.  This corresponds roughly to high school.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (88, NULL, NULL, '"us.census.acs".B15003001', 'Numeric', 'Population 25 Years and Over', 'The number of people in a geographic area who are over the age of 25.  This is used mostly as a denominator of educational attainment.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (89, NULL, NULL, '"us.census.acs".B15003023', 'Numeric', 'Population Completed Master''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a master''s degree, but did not complete a more advanced degree.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (90, NULL, NULL, '"us.census.acs".B15003017', 'Numeric', 'Population Completed High School', 'The number of people in a geographic area over the age of 25 who completed high school, and did not complete a more advanced degree.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (91, NULL, NULL, '"us.census.acs".B15003022', 'Numeric', 'Population Completed Bachelor''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a bachelor''s degree, and did not complete a more advanced degree.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (120, NULL, NULL, '"us.census.acs".B01001016', 'Numeric', 'Men age 50 to 54', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (92, NULL, NULL, '"us.census.acs".B16001001', 'Numeric', 'Population 5 Years and Over', 'The number of people in a geographic area who are over the age of 5.  This is primarily used as a denominator of measures of language spoken at home.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (93, NULL, NULL, '"us.census.acs".B16001003', 'Numeric', 'Speaks Spanish at Home', 'The number of people in a geographic area over age 5 who speak Spanish at home, possibly in addition to other languages.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (94, NULL, NULL, '"us.census.acs".B01001H013', 'Numeric', 'White Men age 55 to 64', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (95, NULL, NULL, '"us.census.acs".B16001002', 'Numeric', 'Speaks only English at Home', 'The number of people in a geographic area over age 5 who speak only English at home.', 3, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (129, NULL, NULL, '"us.census.acs".B01001D012', 'Numeric', 'Asian Men age 45 to 54', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (96, NULL, NULL, '"us.census.acs".B17001001', 'Numeric', 'Population for Whom Poverty Status Determined', 'The number of people in each geography who could be identified as either living in poverty or not.  This should be used as the denominator when calculating poverty rates, as it excludes people for whom it was not possible to determine poverty.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (97, NULL, NULL, '"us.census.acs".B17001002', 'Numeric', 'Income In The Past 12 Months Below Poverty Level', 'The number of people in a geographic area who are part of a family (which could be just them as an individual) determined to be "in poverty" following the Office of Management and Budget''s Directive 14. (https://www.census.gov/hhes/povmeas/methodology/ombdir14.html)', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (98, NULL, NULL, '"us.census.acs".B19013001', 'Numeric', 'Median Household Income in the past 12 Months', 'Within a geographic area, the median income received by every household on a regular basis before payments for personal income taxes, social security, union dues, medicare deductions, etc.  It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans'' (VA) payments, unemployment and/or worker''s compensation, child support, and alimony.', 8, 'median', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (99, NULL, NULL, '"us.census.acs".B19083001', 'Numeric', 'Gini Index', '', 5, '', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (100, NULL, NULL, '"us.census.acs".B19301001', 'Numeric', 'Per Capita Income in the past 12 Months', '', 7, 'average', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (101, NULL, NULL, '"us.census.acs".B25001001', 'Numeric', 'Housing Units', 'A count of housing units in each geography.  A housing unit is a house, an apartment, a mobile home or trailer, a group of rooms, or a single room occupied as separate living quarters, or if vacant, intended for occupancy as separate living quarters.', 8, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (102, NULL, NULL, '"us.census.acs".B25075001', 'Numeric', 'Owner-occupied Housing Units', '', 5, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (103, NULL, NULL, '"us.census.acs".B25081002', 'Numeric', 'Owner-occupied Housing Units with a Mortgage', 'The count of housing units within a geographic area that are mortagaged. "Mortgage" refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust, trust deed, contracts to purchase, land contracts, junior mortgages, and home equity loans.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (104, NULL, NULL, '"us.census.acs".B25002003', 'Numeric', 'Vacant Housing Units', 'The count of vacant housing units in a geographic area. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 8, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (105, NULL, NULL, '"us.census.acs".B25004004', 'Numeric', 'Vacant Housing Units for Sale', 'The count of vacant housing units in a geographic area that are for sale. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (106, NULL, NULL, '"us.census.acs".B25004002', 'Numeric', 'Vacant Housing Units for Rent', 'The count of vacant housing units in a geographic area that are for rent. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 7, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (107, NULL, NULL, '"us.census.acs".B25058001', 'Numeric', 'Median Rent', 'The median contract rent within a geographic area. The contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.', 8, 'median', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (108, NULL, NULL, '"us.census.acs".B25071001', 'Numeric', 'Percent of Household Income Spent on Rent', 'Within a geographic area, the median percentage of household income which was spent on gross rent.  Gross rent is the amount of the contract rent plus the estimated average monthly cost of utilities (electricity, gas, water, sewer etc.) and fuels (oil, coal, wood, etc.) if these are paid by the renter.  Household income is the sum of the income of all people 15 years and older living in the household.', 4, 'average', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (109, NULL, NULL, '"us.census.acs".B25075025', 'Numeric', 'Owner-occupied Housing Units valued at $1,000,000 or more.', 'The count of owner occupied housing units in a geographic area that are valued at $1,000,000 or more.  Value is the respondent''s estimate of how much the property (house and lot, mobile home and lot, or condominium unit) would sell for if it were for sale.', 5, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (110, NULL, NULL, '"us.census.acs".B23008002', 'Numeric', 'Families with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (111, NULL, NULL, 'B23008010', 'Numeric', 'One-parent families, father in labor force, with young children (under 6 years of age)', '', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (112, NULL, NULL, '"us.census.acs".B23008003', 'Numeric', 'Two-parent families with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (113, NULL, NULL, '"us.census.acs".B23008004', 'Numeric', 'Two-parent families, both parents in labor force with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (114, NULL, NULL, '"us.census.acs".B23008005', 'Numeric', 'Two-parent families, father only in labor force with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (115, NULL, NULL, '"us.census.acs".B23008006', 'Numeric', 'Two-parent families, mother only in labor force with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (116, NULL, NULL, '"us.census.acs".B23008007', 'Numeric', 'Two-parent families, neither parent in labor force with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (117, NULL, NULL, '"us.census.acs".B23008008', 'Numeric', 'One-parent families with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (118, NULL, NULL, '"us.census.acs".B23008009', 'Numeric', 'One-parent families, father, with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (121, NULL, NULL, '"us.census.acs".B01001017', 'Numeric', 'Men age 55 to 59', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (122, NULL, NULL, '"us.census.acs".B01001018', 'Numeric', 'Men age 60 to 61', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (123, NULL, NULL, '"us.census.acs".B01001019', 'Numeric', 'Men age 62 to 64', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (124, NULL, NULL, '"us.census.acs".B01001B012', 'Numeric', 'Black Men age 45 to 54', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (125, NULL, NULL, '"us.census.acs".B01001B013', 'Numeric', 'Black Men age 55 to 64', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (126, NULL, NULL, '"us.census.acs".B01001I012', 'Numeric', 'Hispanic Men age 45 to 54', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (127, NULL, NULL, '"us.census.acs".B01001I013', 'Numeric', 'Hispanic Men age 55 to 64', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (168, NULL, NULL, '"us.bls".year', 'Text', 'Year', '4-character year', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (130, NULL, NULL, '"us.census.acs".B01001D013', 'Numeric', 'Asian Men age 55 to 64', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (131, NULL, NULL, '"us.census.acs".B15001028', 'Numeric', 'Men age 45 to 64 who attained less than a 9th grade education', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (132, NULL, NULL, '"us.census.acs".B15001029', 'Numeric', 'Men age 45 to 64 who attained between 9th and 12th grade, no diploma', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (133, NULL, NULL, '"us.census.acs".B15001030', 'Numeric', 'Men age 45 to 64 who completed high school or obtained GED', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (134, NULL, NULL, '"us.census.acs".B15001031', 'Numeric', 'Men age 45 to 64 who completed some college, no degree', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (135, NULL, NULL, '"us.census.acs".B15001032', 'Numeric', 'Men age 45 to 64 who obtained an associate''s degree', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (136, NULL, NULL, '"us.census.acs".B15001033', 'Numeric', 'Men age 45 to 64 who obtained a bachelor''s degree', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (137, NULL, NULL, '"us.census.tiger".zcta5', 'Geometry', 'US Census Zip Code Tabulation Areas', 'ZCTAs are approximate area representations of U.S. Postal Service (USPS) five-digit ZIP Code service areas that the Census Bureau creates using whole blocks to present statistical data from censuses and surveys. The Census Bureau defines ZCTAs by allocating each block that contains addresses to a single ZCTA, usually to the ZCTA that reflects the most frequently occurring ZIP Code for the addresses within that tabulation block. Blocks that do not contain addresses but are completely surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA; those surrounded by multiple ZCTAs will be added to a single ZCTA based on limited buffering performed between multiple ZCTAs. The Census Bureau identifies five-digit ZCTAs using a five-character numeric code that represents the most frequently occurring USPS ZIP Code within that ZCTA, and this code may contain leading zeros.
-
-There are significant changes to the 2010 ZCTA delineation from that used in 2000. Coverage was extended to include the Island Areas for 2010 so that the United States, Puerto Rico, and the Island Areas have ZCTAs. Unlike 2000, when areas that could not be assigned to a ZCTA were given a generic code ending in \u201cXX\u201d (land area) or \u201cHH\u201d (water area), for 2010 there is no universal coverage by ZCTAs, and only legitimate five-digit areas are defined. The 2010 ZCTAs will better represent the actual Zip Code service areas because the Census Bureau initiated a process before creation of 2010 blocks to add block boundaries that split polygons with large numbers of addresses using different Zip Codes.
-
-Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The ZCTAs process used primarily residential addresses and was biased towards Zip Codes used for city-style mail delivery, thus there may be Zip Codes that are primarily nonresidential or boxes only that may not have a corresponding ZCTA.', 6, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (138, NULL, NULL, '"us.census.tiger".block', 'Geometry', 'US Census Blocks', 'Census blocks are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.', 3, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (139, NULL, NULL, '"us.census.tiger".census_tract_geoid', 'Text', 'US Census Tract Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (140, NULL, NULL, '"us.census.tiger".county_geoid', 'Text', 'US County Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (141, NULL, NULL, '"us.census.tiger".congressional_district_geoid', 'Text', 'US Congressional District Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (142, NULL, NULL, '"us.census.tiger".block_geoid', 'Text', 'US Census Block Geoids', NULL, 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (143, NULL, NULL, '"us.census.tiger".zcta5_geoid', 'Text', 'US Census Zip Code Tabulation Area Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (144, NULL, NULL, '"us.census.tiger".puma_geoid', 'Text', 'US Census Public Use Microdata Area Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (145, NULL, NULL, '"us.census.tiger".state_geoid', 'Text', 'US State Geoids', '', 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (146, NULL, NULL, '"us.census.tiger".block_group_geoid', 'Text', 'US Census Block Group Geoids', NULL, 0, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (147, NULL, NULL, '"us.census.lodes".jobs_hispanic', 'Integer', 'Jobs held by workers who are Hispanic or Latino', 'Number of jobs for workers with Ethnicity: Hispanic or Latino', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (148, NULL, NULL, '"us.census.lodes".jobs_less_than_high_school', 'Integer', 'Jobs held by workers who did not complete high school', 'Number of jobs for workers with Educational Attainment: Less than high school', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (149, NULL, NULL, '"us.census.lodes".jobs_high_school', 'Integer', 'Jobs held by workers who completed high school', 'Number of jobs for workers with Educational Attainment: High school or equivalent, no college', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (150, NULL, NULL, '"us.census.lodes".jobs_some_college', 'Integer', 'Jobs held by workers who completed some college or Associate degree', 'Number of jobs for workers with Educational Attainment: Some college or Associate degree', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (151, NULL, NULL, '"us.census.lodes".jobs_bachelors_or_advanced', 'Integer', 'Jobs held by workers who obtained a Bachelor''s degree or advanced degree', 'Number of jobs for workers with Educational Attainment: Bachelor''s degree or advanced degree', 4, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (152, NULL, NULL, '"us.census.lodes".jobs_male', 'Integer', 'Jobs held by men', 'Number of jobs for male workers', 2, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (153, NULL, NULL, '"us.census.lodes".jobs_female', 'Integer', 'Jobs held by women', 'Number of jobs for female workers', 2, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (154, NULL, NULL, '"us.census.lodes".jobs_firm_age_0_1_years', 'Integer', 'Jobs at firms aged 0-1 Years', 'Number of jobs for workers at firms with Firm Age: 0-1 Years', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (155, NULL, NULL, '"us.census.lodes".jobs_firm_age_2_3_years', 'Integer', 'Jobs at firms aged 2-3 Years', 'Number of jobs for workers at firms with Firm Age: 2-3 Years', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (156, NULL, NULL, '"us.census.lodes".jobs_firm_age_4_5_years', 'Integer', 'Jobs at firms aged 4-5 Years', 'Number of jobs for workers at firms with Firm Age: 4-5 Years', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (157, NULL, NULL, '"us.census.lodes".jobs_firm_age_6_10_years', 'Integer', 'Jobs at firms aged 6-10 years', 'Number of jobs for workers at firms with Firm Age: 6-10 Years', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (158, NULL, NULL, '"us.census.lodes".jobs_firm_age_11_more_years', 'Integer', 'Jobs at firms aged 11  Years', 'Number of jobs for workers at firms with Firm Age: 11  Years', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (159, NULL, NULL, '"us.census.lodes".jobs_firm_age_0_19_employees', 'Integer', 'Jobs at firms with 0-19 Employees', 'Number of jobs for workers at firms with Firm Size: 0-19 Employees', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (160, NULL, NULL, '"us.census.lodes".jobs_firm_age_20_49_employees', 'Integer', 'Jobs at firms with 20-49 Employees', 'Number of jobs for workers at firms with Firm Size: 20-49 Employees', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (161, NULL, NULL, '"us.census.lodes".jobs_firm_age_50_249_employees', 'Integer', 'Jobs at firms with 0-249 Employees', 'Number of jobs for workers at firms with Firm Size: 50-249 Employees', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (162, NULL, NULL, '"us.census.lodes".jobs_firm_age_250_499_employees', 'Integer', 'Jobs at firms with 250-499 Employees', 'Number of jobs for workers at firms with Firm Size: 250-499 Employees', 1, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (163, NULL, NULL, '"us.census.lodes".createdate', 'Date', 'Date on which data was created, formatted as YYYYMMDD ', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (164, NULL, NULL, '"us.bls".industry_title', 'Text', 'NAICS Industry Title', 'Title of NAICS industry', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (165, NULL, NULL, '"us.bls".own_code', 'Text', 'Ownership Code', '1-character ownership code: http://www.bls.gov/cew/doc/titles/ownership/ownership_titles.htm', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (166, NULL, NULL, '"us.bls".agglvl_code', 'Text', 'Aggregation Level Code', '2-character aggregation level code: http://www.bls.gov/cew/doc/titles/agglevel/agglevel_titles.htm', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (167, NULL, NULL, '"us.bls".size_code', 'Text', 'Size code', '1-character size code: http://www.bls.gov/cew/doc/titles/size/size_titles.htm', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (169, NULL, NULL, '"us.bls".qtr', 'Text', 'Quarter', '1-character quarter (always A for annual)', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (170, NULL, NULL, '"us.bls".disclosure_code', 'Text', 'Disclosure code', '1-character disclosure code (either '' ''(blank)), or ''N'' not disclosed)', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (171, NULL, NULL, '"us.bls".qtrly_estabs', 'Numeric', 'Establishment count', 'Count of establishments for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (172, NULL, NULL, '"us.bls".month1_emplvl', 'Numeric', 'First month employment', 'Employment level for the first month of a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (173, NULL, NULL, '"us.bls".month2_emplvl', 'Numeric', 'Second month employment', 'Employment level for the second month of a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (174, NULL, NULL, '"us.bls".month3_emplvl', 'Numeric', 'Third month employment', 'Employment level for the third month of a  given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (175, NULL, NULL, '"us.bls".total_qtrly_wages', 'Numeric', 'Total wages', 'Total wages for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (176, NULL, NULL, '"us.bls".taxable_qtrly_wages', 'Numeric', 'Taxable wages', 'Taxable wages for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (177, NULL, NULL, '"us.bls".qtrly_contributions', 'Numeric', 'Total contributions', 'Quarterly contributions for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (178, NULL, NULL, '"us.bls".avg_wkly_wage', 'Numeric', 'Average weekly wage', 'Average weekly wage for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (179, NULL, NULL, '"us.bls".lq_disclosure_code', 'Text', 'Location quotient disclosure code', '1-character location-quotient disclosure code (either '' ''(blank)), or ''N'' not disclosed', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (180, NULL, NULL, '"us.bls".lq_qtrly_estabs', 'Numeric', 'Location quotient', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (181, NULL, NULL, '"us.bls".lq_month1_emplvl', 'Numeric', 'Location quotient first month', 'Location quotient of the employment level for the first month of a given quarter relative to the U.S. (Rounded to hundredths place)),', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (182, NULL, NULL, '"us.bls".lq_month2_emplvl', 'Numeric', 'Location quotient second month', 'Location quotient of the employment level for the second month of a given quarter relative to the U.S. (Rounded to hundredths place)),', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (183, NULL, NULL, '"us.bls".lq_month3_emplvl', 'Numeric', 'Location quotient third month', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)),', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (184, NULL, NULL, '"us.bls".lq_total_qtrly_wages', 'Numeric', 'Location quotient quarterly', 'Location quotient of the total wages for a given quarter relative to the U.S. (Rounded to hundredths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (185, NULL, NULL, '"us.bls".lq_taxable_qtrly_wages', 'Numeric', 'Quarterly location quotient taxable wages', 'Location quotient of the total taxable wages for a given quarter relative to the U.S. (Rounded to hundredths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (186, NULL, NULL, '"us.bls".lq_qtrly_contributions', 'Numeric', 'Quarterly location quotient contributions', 'Location quotient of the total contributions for a given quarter relative to the U.S. (Rounded to hundredths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (187, NULL, NULL, '"us.bls".lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (188, NULL, NULL, '"us.bls".oty_disclosure_code', 'Text', 'Over-the-year Disclosure code', '1-character over-the-year disclosure code (either '' ''(blank)), or ''N'' not disclosed)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (189, NULL, NULL, '"us.bls".oty_qtrly_estabs_chg', 'Numeric', 'Over-the-year change in establishment count', 'Over-the-year change in the count of establishments for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (190, NULL, NULL, '"us.bls".oty_qtrly_estabs_pct_chg', 'Numeric', 'Over-the-year percent change in establishment count', 'Over-the-year percent change in the count of establishments for a given quarter (Rounded to the tenths place)', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (191, NULL, NULL, '"us.bls".oty_month1_emplvl_chg', 'Numeric', 'Over-the-year change in first month employment level', 'Over-the-year change in the first month''s employment level of a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (192, NULL, NULL, '"us.bls".oty_month1_emplvl_pct_chg', 'Numeric', 'Over-the-year percent change in first month employment level', 'Over-the-year percent change in the first month''s employment level of a given quarter (Rounded to the tenths place)),', 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (193, NULL, NULL, '"us.bls".oty_month2_emplvl_chg', 'Numeric', 'Over-the-year change in second month employment level', 'Over-the-year change in the second month''s employment level of a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (194, NULL, NULL, '"us.bls".oty_month2_emplvl_pct_chg', 'Numeric', 'Over-the-year percent change in second month employment level', 'Over-the-year percent change in the second month''s employment level of a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (195, NULL, NULL, '"us.bls".oty_month3_emplvl_chg', 'Numeric', 'Over-the-year change in third month employment level', 'Over-the-year change in the third month''s employment level of a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (196, NULL, NULL, '"us.bls".oty_month3_emplvl_pct_chg', 'Numeric', 'Over-the-year percent change in third month employment level', 'Over-the-year percent change in the third month''s employment level of a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (197, NULL, NULL, '"us.bls".oty_total_qtrly_wages_chg', 'Numeric', 'Over-the-year change in total quarterly wages', 'Over-the-year change in total quarterly wages for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (198, NULL, NULL, '"us.bls".oty_total_qtrly_wages_pct_chg', 'Numeric', 'Over-the-year percent change in total quarterly wages', 'Over-the-year percent change in total quarterly wages for a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (199, NULL, NULL, '"us.bls".oty_taxable_qtrly_wages_chg', 'Numeric', 'Over-the-year change in taxable quarterly wages', 'Over-the-year change in taxable quarterly wages for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (200, NULL, NULL, '"us.bls".oty_taxable_qtrly_wages_pct_chg', 'Numeric', 'Over-the-year percent change in taxable quarterly wages', 'Over-the-year percent change in taxable quarterly wages for a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (201, NULL, NULL, '"us.bls".oty_qtrly_contributions_chg', 'Numeric', 'Over-the-year change in quarterly contributions', 'Over-the-year change in quarterly contributions for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (202, NULL, NULL, '"us.bls".oty_qtrly_contributions_pct_chg', 'Numeric', 'Over-the-year percent change in quarterly contributions', 'Over-the-year percent change in quarterly contributions for a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (203, NULL, NULL, '"us.bls".oty_avg_wkly_wage_chg', 'Numeric', 'Over-the-year change in average weekly wage', 'Over-the-year change in average weekly wage for a given quarter', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (204, NULL, NULL, '"us.bls".oty_avg_wkly_wage_pct_chg', 'Numeric', 'Over-the-year percent change in average weekly wage', 'Over-the-year percent change in average weekly wage for a given quarter (Rounded to the tenths place)', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (205, NULL, NULL, '"us.bls".total_all_industries_avg_wkly_wage', 'Numeric', 'Average weekly wage for Total, all industries', 'Average weekly wage for a given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (206, NULL, NULL, '"us.bls".total_all_industries_qtrly_estabs', 'Numeric', 'Establishment count for Total, all industries', 'Count of establishments for a given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (207, NULL, NULL, '"us.bls".total_all_industries_month3_emplvl', 'Numeric', 'Third month employment for Total, all industries', 'Employment level for the third month of a  given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (208, NULL, NULL, '"us.bls".total_all_industries_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Total, all industries', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (209, NULL, NULL, '"us.bls".total_all_industries_lq_qtrly_estabs', 'Numeric', 'Location quotient for Total, all industries', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (210, NULL, NULL, '"us.bls".total_all_industries_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Total, all industries', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (211, NULL, NULL, '"us.bls".natural_resources_and_mining_avg_wkly_wage', 'Numeric', 'Average weekly wage for Natural resources and mining', 'Average weekly wage for a given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (212, NULL, NULL, '"us.bls".natural_resources_and_mining_qtrly_estabs', 'Numeric', 'Establishment count for Natural resources and mining', 'Count of establishments for a given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (213, NULL, NULL, '"us.bls".natural_resources_and_mining_month3_emplvl', 'Numeric', 'Third month employment for Natural resources and mining', 'Employment level for the third month of a  given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (214, NULL, NULL, '"us.bls".natural_resources_and_mining_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Natural resources and mining', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (215, NULL, NULL, '"us.bls".natural_resources_and_mining_lq_qtrly_estabs', 'Numeric', 'Location quotient for Natural resources and mining', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (216, NULL, NULL, '"us.bls".natural_resources_and_mining_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Natural resources and mining', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (217, NULL, NULL, '"us.bls".construction_avg_wkly_wage', 'Numeric', 'Average weekly wage for Construction', 'Average weekly wage for a given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (218, NULL, NULL, '"us.bls".construction_qtrly_estabs', 'Numeric', 'Establishment count for Construction', 'Count of establishments for a given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (219, NULL, NULL, '"us.bls".construction_month3_emplvl', 'Numeric', 'Third month employment for Construction', 'Employment level for the third month of a  given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (220, NULL, NULL, '"us.bls".construction_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Construction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (221, NULL, NULL, '"us.bls".construction_lq_qtrly_estabs', 'Numeric', 'Location quotient for Construction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (222, NULL, NULL, '"us.bls".construction_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Construction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (223, NULL, NULL, '"us.bls".manufacturing_avg_wkly_wage', 'Numeric', 'Average weekly wage for Manufacturing', 'Average weekly wage for a given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (224, NULL, NULL, '"us.bls".manufacturing_qtrly_estabs', 'Numeric', 'Establishment count for Manufacturing', 'Count of establishments for a given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (225, NULL, NULL, '"us.bls".manufacturing_month3_emplvl', 'Numeric', 'Third month employment for Manufacturing', 'Employment level for the third month of a  given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (226, NULL, NULL, '"us.bls".manufacturing_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Manufacturing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (227, NULL, NULL, '"us.bls".manufacturing_lq_qtrly_estabs', 'Numeric', 'Location quotient for Manufacturing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (228, NULL, NULL, '"us.bls".manufacturing_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Manufacturing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (229, NULL, NULL, '"us.bls".trade_transportation_and_utilities_avg_wkly_wage', 'Numeric', 'Average weekly wage for Trade, transportation, and utilities', 'Average weekly wage for a given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (230, NULL, NULL, '"us.bls".trade_transportation_and_utilities_qtrly_estabs', 'Numeric', 'Establishment count for Trade, transportation, and utilities', 'Count of establishments for a given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (259, NULL, NULL, '"us.bls".leisure_and_hospitality_avg_wkly_wage', 'Numeric', 'Average weekly wage for Leisure and hospitality', 'Average weekly wage for a given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (231, NULL, NULL, '"us.bls".trade_transportation_and_utilities_month3_emplvl', 'Numeric', 'Third month employment for Trade, transportation, and utilities', 'Employment level for the third month of a  given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (232, NULL, NULL, '"us.bls".trade_transportation_and_utilities_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Trade, transportation, and utilities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (233, NULL, NULL, '"us.bls".trade_transportation_and_utilities_lq_qtrly_estabs', 'Numeric', 'Location quotient for Trade, transportation, and utilities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (234, NULL, NULL, '"us.bls".trade_transportation_and_utilities_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Trade, transportation, and utilities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (235, NULL, NULL, '"us.bls".information_avg_wkly_wage', 'Numeric', 'Average weekly wage for Information', 'Average weekly wage for a given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (236, NULL, NULL, '"us.bls".information_qtrly_estabs', 'Numeric', 'Establishment count for Information', 'Count of establishments for a given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (237, NULL, NULL, '"us.bls".information_month3_emplvl', 'Numeric', 'Third month employment for Information', 'Employment level for the third month of a  given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (238, NULL, NULL, '"us.bls".information_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Information', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (239, NULL, NULL, '"us.bls".information_lq_qtrly_estabs', 'Numeric', 'Location quotient for Information', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (240, NULL, NULL, '"us.bls".information_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Information', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (241, NULL, NULL, '"us.bls".financial_activities_avg_wkly_wage', 'Numeric', 'Average weekly wage for Financial activities', 'Average weekly wage for a given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (242, NULL, NULL, '"us.bls".financial_activities_qtrly_estabs', 'Numeric', 'Establishment count for Financial activities', 'Count of establishments for a given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (243, NULL, NULL, '"us.bls".financial_activities_month3_emplvl', 'Numeric', 'Third month employment for Financial activities', 'Employment level for the third month of a  given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (244, NULL, NULL, '"us.bls".financial_activities_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Financial activities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (245, NULL, NULL, '"us.bls".financial_activities_lq_qtrly_estabs', 'Numeric', 'Location quotient for Financial activities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (246, NULL, NULL, '"us.bls".financial_activities_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Financial activities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (247, NULL, NULL, '"us.bls".professional_and_business_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for Professional and business services', 'Average weekly wage for a given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (248, NULL, NULL, '"us.bls".professional_and_business_services_qtrly_estabs', 'Numeric', 'Establishment count for Professional and business services', 'Count of establishments for a given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (249, NULL, NULL, '"us.bls".professional_and_business_services_month3_emplvl', 'Numeric', 'Third month employment for Professional and business services', 'Employment level for the third month of a  given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (250, NULL, NULL, '"us.bls".professional_and_business_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Professional and business services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (251, NULL, NULL, '"us.bls".professional_and_business_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for Professional and business services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (252, NULL, NULL, '"us.bls".professional_and_business_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Professional and business services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (253, NULL, NULL, '"us.bls".education_and_health_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for Education and health services', 'Average weekly wage for a given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (254, NULL, NULL, '"us.bls".education_and_health_services_qtrly_estabs', 'Numeric', 'Establishment count for Education and health services', 'Count of establishments for a given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (255, NULL, NULL, '"us.bls".education_and_health_services_month3_emplvl', 'Numeric', 'Third month employment for Education and health services', 'Employment level for the third month of a  given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (256, NULL, NULL, '"us.bls".education_and_health_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Education and health services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (257, NULL, NULL, '"us.bls".education_and_health_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for Education and health services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (258, NULL, NULL, '"us.bls".education_and_health_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Education and health services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (260, NULL, NULL, '"us.bls".leisure_and_hospitality_qtrly_estabs', 'Numeric', 'Establishment count for Leisure and hospitality', 'Count of establishments for a given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (261, NULL, NULL, '"us.bls".leisure_and_hospitality_month3_emplvl', 'Numeric', 'Third month employment for Leisure and hospitality', 'Employment level for the third month of a  given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (262, NULL, NULL, '"us.bls".leisure_and_hospitality_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Leisure and hospitality', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (263, NULL, NULL, '"us.bls".leisure_and_hospitality_lq_qtrly_estabs', 'Numeric', 'Location quotient for Leisure and hospitality', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (264, NULL, NULL, '"us.bls".leisure_and_hospitality_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Leisure and hospitality', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (265, NULL, NULL, '"us.bls".other_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for Other services', 'Average weekly wage for a given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (266, NULL, NULL, '"us.bls".other_services_qtrly_estabs', 'Numeric', 'Establishment count for Other services', 'Count of establishments for a given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (267, NULL, NULL, '"us.bls".other_services_month3_emplvl', 'Numeric', 'Third month employment for Other services', 'Employment level for the third month of a  given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (268, NULL, NULL, '"us.bls".other_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Other services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (269, NULL, NULL, '"us.bls".other_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for Other services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (270, NULL, NULL, '"us.bls".other_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Other services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (271, NULL, NULL, '"us.bls".public_administration_avg_wkly_wage', 'Numeric', 'Average weekly wage for Public administration', 'Average weekly wage for a given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (272, NULL, NULL, '"us.bls".public_administration_qtrly_estabs', 'Numeric', 'Establishment count for Public administration', 'Count of establishments for a given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (273, NULL, NULL, '"us.bls".public_administration_month3_emplvl', 'Numeric', 'Third month employment for Public administration', 'Employment level for the third month of a  given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (274, NULL, NULL, '"us.bls".public_administration_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (275, NULL, NULL, '"us.bls".public_administration_lq_qtrly_estabs', 'Numeric', 'Location quotient for Public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (276, NULL, NULL, '"us.bls".public_administration_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (277, NULL, NULL, '"us.bls".unclassified_avg_wkly_wage', 'Numeric', 'Average weekly wage for Unclassified', 'Average weekly wage for a given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (278, NULL, NULL, '"us.bls".unclassified_qtrly_estabs', 'Numeric', 'Establishment count for Unclassified', 'Count of establishments for a given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (279, NULL, NULL, '"us.bls".unclassified_month3_emplvl', 'Numeric', 'Third month employment for Unclassified', 'Employment level for the third month of a  given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (280, NULL, NULL, '"us.bls".unclassified_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for Unclassified', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (281, NULL, NULL, '"us.bls".unclassified_lq_qtrly_estabs', 'Numeric', 'Location quotient for Unclassified', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (282, NULL, NULL, '"us.bls".unclassified_lq_month3_emplvl', 'Numeric', 'Location quotient third month for Unclassified', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (283, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 11 Agriculture, forestry, fishing and hunting', 'Average weekly wage for a given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (284, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 11 Agriculture, forestry, fishing and hunting', 'Count of establishments for a given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (285, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_month3_emplvl', 'Numeric', 'Third month employment for NAICS 11 Agriculture, forestry, fishing and hunting', 'Employment level for the third month of a  given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (286, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (287, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (315, NULL, NULL, '"us.bls".naics_51_information_month3_emplvl', 'Numeric', 'Third month employment for NAICS 51 Information', 'Employment level for the third month of a  given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (288, NULL, NULL, '"us.bls".naics_11_agriculture_forestry_fishing_and_hunting_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (289, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Average weekly wage for a given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (290, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Count of establishments for a given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (291, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_month3_emplvl', 'Numeric', 'Third month employment for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Employment level for the third month of a  given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (292, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (293, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (294, NULL, NULL, '"us.bls".naics_21_mining_quarrying_and_oil_and_gas_extraction_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (295, NULL, NULL, '"us.bls".naics_22_utilities_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 22 Utilities', 'Average weekly wage for a given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (296, NULL, NULL, '"us.bls".naics_22_utilities_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 22 Utilities', 'Count of establishments for a given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (297, NULL, NULL, '"us.bls".naics_22_utilities_month3_emplvl', 'Numeric', 'Third month employment for NAICS 22 Utilities', 'Employment level for the third month of a  given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (298, NULL, NULL, '"us.bls".naics_22_utilities_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 22 Utilities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (299, NULL, NULL, '"us.bls".naics_22_utilities_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 22 Utilities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (300, NULL, NULL, '"us.bls".naics_22_utilities_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 22 Utilities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (301, NULL, NULL, '"us.bls".naics_23_construction_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 23 Construction', 'Average weekly wage for a given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (302, NULL, NULL, '"us.bls".naics_23_construction_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 23 Construction', 'Count of establishments for a given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (303, NULL, NULL, '"us.bls".naics_23_construction_month3_emplvl', 'Numeric', 'Third month employment for NAICS 23 Construction', 'Employment level for the third month of a  given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (304, NULL, NULL, '"us.bls".naics_23_construction_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 23 Construction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (305, NULL, NULL, '"us.bls".naics_23_construction_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 23 Construction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (306, NULL, NULL, '"us.bls".naics_23_construction_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 23 Construction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (307, NULL, NULL, '"us.bls".naics_42_wholesale_trade_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 42 Wholesale trade', 'Average weekly wage for a given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (308, NULL, NULL, '"us.bls".naics_42_wholesale_trade_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 42 Wholesale trade', 'Count of establishments for a given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (309, NULL, NULL, '"us.bls".naics_42_wholesale_trade_month3_emplvl', 'Numeric', 'Third month employment for NAICS 42 Wholesale trade', 'Employment level for the third month of a  given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (310, NULL, NULL, '"us.bls".naics_42_wholesale_trade_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 42 Wholesale trade', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (311, NULL, NULL, '"us.bls".naics_42_wholesale_trade_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 42 Wholesale trade', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (312, NULL, NULL, '"us.bls".naics_42_wholesale_trade_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 42 Wholesale trade', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (313, NULL, NULL, '"us.bls".naics_51_information_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 51 Information', 'Average weekly wage for a given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (314, NULL, NULL, '"us.bls".naics_51_information_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 51 Information', 'Count of establishments for a given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (316, NULL, NULL, '"us.bls".naics_51_information_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 51 Information', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (317, NULL, NULL, '"us.bls".naics_51_information_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 51 Information', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (538, NULL, NULL, '"us.bls".month3_emplvl_naics51', 'Numeric', 'Third month employment for NAICS 51 Information', 'Employment level for the third month of a  given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (318, NULL, NULL, '"us.bls".naics_51_information_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 51 Information', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (319, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 52 Finance and insurance', 'Average weekly wage for a given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (320, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 52 Finance and insurance', 'Count of establishments for a given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (321, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_month3_emplvl', 'Numeric', 'Third month employment for NAICS 52 Finance and insurance', 'Employment level for the third month of a  given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (322, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 52 Finance and insurance', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (323, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 52 Finance and insurance', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (324, NULL, NULL, '"us.bls".naics_52_finance_and_insurance_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 52 Finance and insurance', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (325, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 53 Real estate and rental and leasing', 'Average weekly wage for a given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (326, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 53 Real estate and rental and leasing', 'Count of establishments for a given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (327, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_month3_emplvl', 'Numeric', 'Third month employment for NAICS 53 Real estate and rental and leasing', 'Employment level for the third month of a  given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (328, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 53 Real estate and rental and leasing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (329, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 53 Real estate and rental and leasing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (330, NULL, NULL, '"us.bls".naics_53_real_estate_and_rental_and_leasing_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 53 Real estate and rental and leasing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (331, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 54 Professional and technical services', 'Average weekly wage for a given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (332, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 54 Professional and technical services', 'Count of establishments for a given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (333, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_month3_emplvl', 'Numeric', 'Third month employment for NAICS 54 Professional and technical services', 'Employment level for the third month of a  given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (334, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 54 Professional and technical services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (335, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 54 Professional and technical services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (336, NULL, NULL, '"us.bls".naics_54_professional_and_technical_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 54 Professional and technical services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (337, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 55 Management of companies and enterprises', 'Average weekly wage for a given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (338, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 55 Management of companies and enterprises', 'Count of establishments for a given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (339, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_month3_emplvl', 'Numeric', 'Third month employment for NAICS 55 Management of companies and enterprises', 'Employment level for the third month of a  given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (415, NULL, NULL, '"us.bls".avg_wkly_wage_naics1011', 'Numeric', 'Average weekly wage for Natural resources and mining', 'Average weekly wage for a given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (340, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 55 Management of companies and enterprises', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (389, NULL, NULL, '"us.bls".naics_99_unclassified_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 99 Unclassified', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (341, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 55 Management of companies and enterprises', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (342, NULL, NULL, '"us.bls".naics_55_management_of_companies_and_enterprises_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 55 Management of companies and enterprises', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (343, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 56 Administrative and waste services', 'Average weekly wage for a given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (344, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 56 Administrative and waste services', 'Count of establishments for a given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (345, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_month3_emplvl', 'Numeric', 'Third month employment for NAICS 56 Administrative and waste services', 'Employment level for the third month of a  given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (346, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 56 Administrative and waste services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (347, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 56 Administrative and waste services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (348, NULL, NULL, '"us.bls".naics_56_administrative_and_waste_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 56 Administrative and waste services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (349, NULL, NULL, '"us.bls".naics_61_educational_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 61 Educational services', 'Average weekly wage for a given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (350, NULL, NULL, '"us.bls".naics_61_educational_services_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 61 Educational services', 'Count of establishments for a given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (351, NULL, NULL, '"us.bls".naics_61_educational_services_month3_emplvl', 'Numeric', 'Third month employment for NAICS 61 Educational services', 'Employment level for the third month of a  given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (352, NULL, NULL, '"us.bls".naics_61_educational_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 61 Educational services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (353, NULL, NULL, '"us.bls".naics_61_educational_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 61 Educational services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (354, NULL, NULL, '"us.bls".naics_61_educational_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 61 Educational services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (355, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 62 Health care and social assistance', 'Average weekly wage for a given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (356, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 62 Health care and social assistance', 'Count of establishments for a given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (357, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_month3_emplvl', 'Numeric', 'Third month employment for NAICS 62 Health care and social assistance', 'Employment level for the third month of a  given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (358, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 62 Health care and social assistance', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (359, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 62 Health care and social assistance', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (360, NULL, NULL, '"us.bls".naics_62_health_care_and_social_assistance_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 62 Health care and social assistance', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (361, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 71 Arts, entertainment, and recreation', 'Average weekly wage for a given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (362, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 71 Arts, entertainment, and recreation', 'Count of establishments for a given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (363, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_month3_emplvl', 'Numeric', 'Third month employment for NAICS 71 Arts, entertainment, and recreation', 'Employment level for the third month of a  given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (701, NULL, NULL, '"us.census.acs".B01001002_quantile', 'Numeric', 'Quantile:Male Population', 'The number of people within each geography who are male.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (364, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (365, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (366, NULL, NULL, '"us.bls".naics_71_arts_entertainment_and_recreation_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (367, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 72 Accommodation and food services', 'Average weekly wage for a given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (368, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 72 Accommodation and food services', 'Count of establishments for a given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (369, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_month3_emplvl', 'Numeric', 'Third month employment for NAICS 72 Accommodation and food services', 'Employment level for the third month of a  given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (370, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 72 Accommodation and food services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (371, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 72 Accommodation and food services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (372, NULL, NULL, '"us.bls".naics_72_accommodation_and_food_services_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 72 Accommodation and food services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (373, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 81 Other services, except public administration', 'Average weekly wage for a given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (374, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 81 Other services, except public administration', 'Count of establishments for a given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (375, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_month3_emplvl', 'Numeric', 'Third month employment for NAICS 81 Other services, except public administration', 'Employment level for the third month of a  given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (376, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 81 Other services, except public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (377, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 81 Other services, except public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (378, NULL, NULL, '"us.bls".naics_81_other_services_except_public_administration_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 81 Other services, except public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (379, NULL, NULL, '"us.bls".naics_92_public_administration_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 92 Public administration', 'Average weekly wage for a given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (380, NULL, NULL, '"us.bls".naics_92_public_administration_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 92 Public administration', 'Count of establishments for a given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (381, NULL, NULL, '"us.bls".naics_92_public_administration_month3_emplvl', 'Numeric', 'Third month employment for NAICS 92 Public administration', 'Employment level for the third month of a  given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (382, NULL, NULL, '"us.bls".naics_92_public_administration_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 92 Public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (383, NULL, NULL, '"us.bls".naics_92_public_administration_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 92 Public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (384, NULL, NULL, '"us.bls".naics_92_public_administration_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 92 Public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (385, NULL, NULL, '"us.bls".naics_99_unclassified_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 99 Unclassified', 'Average weekly wage for a given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (386, NULL, NULL, '"us.bls".naics_99_unclassified_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 99 Unclassified', 'Count of establishments for a given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (387, NULL, NULL, '"us.bls".naics_99_unclassified_month3_emplvl', 'Numeric', 'Third month employment for NAICS 99 Unclassified', 'Employment level for the third month of a  given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (416, NULL, NULL, '"us.bls".qtrly_estabs_naics1011', 'Numeric', 'Establishment count for Natural resources and mining', 'Count of establishments for a given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (388, NULL, NULL, '"us.bls".naics_99_unclassified_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 99 Unclassified', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (390, NULL, NULL, '"us.bls".naics_99_unclassified_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 99 Unclassified', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (391, NULL, NULL, '"us.bls".naics_31_33_manufacturing_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 31-33 Manufacturing', 'Average weekly wage for a given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (392, NULL, NULL, '"us.bls".naics_31_33_manufacturing_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 31-33 Manufacturing', 'Count of establishments for a given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (393, NULL, NULL, '"us.bls".naics_31_33_manufacturing_month3_emplvl', 'Numeric', 'Third month employment for NAICS 31-33 Manufacturing', 'Employment level for the third month of a  given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (394, NULL, NULL, '"us.bls".naics_31_33_manufacturing_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 31-33 Manufacturing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (395, NULL, NULL, '"us.bls".naics_31_33_manufacturing_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 31-33 Manufacturing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (396, NULL, NULL, '"us.bls".naics_31_33_manufacturing_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 31-33 Manufacturing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (397, NULL, NULL, '"us.bls".naics_44_45_retail_trade_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 44-45 Retail trade', 'Average weekly wage for a given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (398, NULL, NULL, '"us.bls".naics_44_45_retail_trade_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 44-45 Retail trade', 'Count of establishments for a given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (399, NULL, NULL, '"us.bls".naics_44_45_retail_trade_month3_emplvl', 'Numeric', 'Third month employment for NAICS 44-45 Retail trade', 'Employment level for the third month of a  given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (400, NULL, NULL, '"us.bls".naics_44_45_retail_trade_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 44-45 Retail trade', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (401, NULL, NULL, '"us.bls".naics_44_45_retail_trade_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 44-45 Retail trade', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (402, NULL, NULL, '"us.bls".naics_44_45_retail_trade_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 44-45 Retail trade', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (403, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_avg_wkly_wage', 'Numeric', 'Average weekly wage for NAICS 48-49 Transportation and warehousing', 'Average weekly wage for a given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (404, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_qtrly_estabs', 'Numeric', 'Establishment count for NAICS 48-49 Transportation and warehousing', 'Count of establishments for a given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (405, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_month3_emplvl', 'Numeric', 'Third month employment for NAICS 48-49 Transportation and warehousing', 'Employment level for the third month of a  given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (406, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_lq_avg_wkly_wage', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 48-49 Transportation and warehousing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (407, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_lq_qtrly_estabs', 'Numeric', 'Location quotient for NAICS 48-49 Transportation and warehousing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (408, NULL, NULL, '"us.bls".naics_48_49_transportation_and_warehousing_lq_month3_emplvl', 'Numeric', 'Location quotient third month for NAICS 48-49 Transportation and warehousing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (409, NULL, NULL, '"us.bls".avg_wkly_wage_naics10', 'Numeric', 'Average weekly wage for Total, all industries', 'Average weekly wage for a given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (410, NULL, NULL, '"us.bls".qtrly_estabs_naics10', 'Numeric', 'Establishment count for Total, all industries', 'Count of establishments for a given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (411, NULL, NULL, '"us.bls".month3_emplvl_naics10', 'Numeric', 'Third month employment for Total, all industries', 'Employment level for the third month of a  given quarter for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (412, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics10', 'Numeric', 'Quarterly location quotient weekly wage for Total, all industries', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (413, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics10', 'Numeric', 'Location quotient for Total, all industries', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (414, NULL, NULL, '"us.bls".lq_month3_emplvl_naics10', 'Numeric', 'Location quotient third month for Total, all industries', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Total, all industries', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (417, NULL, NULL, '"us.bls".month3_emplvl_naics1011', 'Numeric', 'Third month employment for Natural resources and mining', 'Employment level for the third month of a  given quarter for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (418, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1011', 'Numeric', 'Quarterly location quotient weekly wage for Natural resources and mining', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (419, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1011', 'Numeric', 'Location quotient for Natural resources and mining', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (420, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1011', 'Numeric', 'Location quotient third month for Natural resources and mining', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Natural resources and mining', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (421, NULL, NULL, '"us.bls".avg_wkly_wage_naics1012', 'Numeric', 'Average weekly wage for Construction', 'Average weekly wage for a given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (422, NULL, NULL, '"us.bls".qtrly_estabs_naics1012', 'Numeric', 'Establishment count for Construction', 'Count of establishments for a given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (423, NULL, NULL, '"us.bls".month3_emplvl_naics1012', 'Numeric', 'Third month employment for Construction', 'Employment level for the third month of a  given quarter for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (424, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1012', 'Numeric', 'Quarterly location quotient weekly wage for Construction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (425, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1012', 'Numeric', 'Location quotient for Construction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (426, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1012', 'Numeric', 'Location quotient third month for Construction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (427, NULL, NULL, '"us.bls".avg_wkly_wage_naics1013', 'Numeric', 'Average weekly wage for Manufacturing', 'Average weekly wage for a given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (428, NULL, NULL, '"us.bls".qtrly_estabs_naics1013', 'Numeric', 'Establishment count for Manufacturing', 'Count of establishments for a given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (429, NULL, NULL, '"us.bls".month3_emplvl_naics1013', 'Numeric', 'Third month employment for Manufacturing', 'Employment level for the third month of a  given quarter for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (430, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1013', 'Numeric', 'Quarterly location quotient weekly wage for Manufacturing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (431, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1013', 'Numeric', 'Location quotient for Manufacturing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (432, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1013', 'Numeric', 'Location quotient third month for Manufacturing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (433, NULL, NULL, '"us.bls".avg_wkly_wage_naics1021', 'Numeric', 'Average weekly wage for Trade, transportation, and utilities', 'Average weekly wage for a given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (434, NULL, NULL, '"us.bls".qtrly_estabs_naics1021', 'Numeric', 'Establishment count for Trade, transportation, and utilities', 'Count of establishments for a given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (435, NULL, NULL, '"us.bls".month3_emplvl_naics1021', 'Numeric', 'Third month employment for Trade, transportation, and utilities', 'Employment level for the third month of a  given quarter for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (436, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1021', 'Numeric', 'Quarterly location quotient weekly wage for Trade, transportation, and utilities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (437, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1021', 'Numeric', 'Location quotient for Trade, transportation, and utilities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (438, NULL, NULL, '"us.bls".qtrly_estabs_naics1027', 'Numeric', 'Establishment count for Other services', 'Count of establishments for a given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (439, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1021', 'Numeric', 'Location quotient third month for Trade, transportation, and utilities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Trade, transportation, and utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (440, NULL, NULL, '"us.bls".avg_wkly_wage_naics1022', 'Numeric', 'Average weekly wage for Information', 'Average weekly wage for a given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (441, NULL, NULL, '"us.bls".qtrly_estabs_naics1022', 'Numeric', 'Establishment count for Information', 'Count of establishments for a given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (442, NULL, NULL, '"us.bls".month3_emplvl_naics1022', 'Numeric', 'Third month employment for Information', 'Employment level for the third month of a  given quarter for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (443, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1022', 'Numeric', 'Quarterly location quotient weekly wage for Information', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (444, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1022', 'Numeric', 'Location quotient for Information', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (445, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1022', 'Numeric', 'Location quotient third month for Information', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (446, NULL, NULL, '"us.bls".avg_wkly_wage_naics1023', 'Numeric', 'Average weekly wage for Financial activities', 'Average weekly wage for a given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (447, NULL, NULL, '"us.bls".qtrly_estabs_naics1023', 'Numeric', 'Establishment count for Financial activities', 'Count of establishments for a given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (448, NULL, NULL, '"us.bls".month3_emplvl_naics1023', 'Numeric', 'Third month employment for Financial activities', 'Employment level for the third month of a  given quarter for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (449, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1023', 'Numeric', 'Quarterly location quotient weekly wage for Financial activities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (450, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1023', 'Numeric', 'Location quotient for Financial activities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (451, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1023', 'Numeric', 'Location quotient third month for Financial activities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Financial activities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (452, NULL, NULL, '"us.bls".avg_wkly_wage_naics1024', 'Numeric', 'Average weekly wage for Professional and business services', 'Average weekly wage for a given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (453, NULL, NULL, '"us.bls".qtrly_estabs_naics1024', 'Numeric', 'Establishment count for Professional and business services', 'Count of establishments for a given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (454, NULL, NULL, '"us.bls".month3_emplvl_naics1024', 'Numeric', 'Third month employment for Professional and business services', 'Employment level for the third month of a  given quarter for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (455, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1024', 'Numeric', 'Quarterly location quotient weekly wage for Professional and business services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (456, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1024', 'Numeric', 'Location quotient for Professional and business services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (457, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1024', 'Numeric', 'Location quotient third month for Professional and business services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Professional and business services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (458, NULL, NULL, '"us.bls".avg_wkly_wage_naics1025', 'Numeric', 'Average weekly wage for Education and health services', 'Average weekly wage for a given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (459, NULL, NULL, '"us.bls".qtrly_estabs_naics1025', 'Numeric', 'Establishment count for Education and health services', 'Count of establishments for a given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (460, NULL, NULL, '"us.bls".month3_emplvl_naics1025', 'Numeric', 'Third month employment for Education and health services', 'Employment level for the third month of a  given quarter for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (461, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1025', 'Numeric', 'Quarterly location quotient weekly wage for Education and health services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (462, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1025', 'Numeric', 'Location quotient for Education and health services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (463, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1025', 'Numeric', 'Location quotient third month for Education and health services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Education and health services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (464, NULL, NULL, '"us.bls".avg_wkly_wage_naics1026', 'Numeric', 'Average weekly wage for Leisure and hospitality', 'Average weekly wage for a given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (465, NULL, NULL, '"us.bls".qtrly_estabs_naics1026', 'Numeric', 'Establishment count for Leisure and hospitality', 'Count of establishments for a given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (466, NULL, NULL, '"us.bls".month3_emplvl_naics1026', 'Numeric', 'Third month employment for Leisure and hospitality', 'Employment level for the third month of a  given quarter for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (467, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1026', 'Numeric', 'Quarterly location quotient weekly wage for Leisure and hospitality', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (468, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1026', 'Numeric', 'Location quotient for Leisure and hospitality', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (469, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1026', 'Numeric', 'Location quotient third month for Leisure and hospitality', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Leisure and hospitality', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (470, NULL, NULL, '"us.bls".avg_wkly_wage_naics1027', 'Numeric', 'Average weekly wage for Other services', 'Average weekly wage for a given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (471, NULL, NULL, '"us.bls".month3_emplvl_naics1027', 'Numeric', 'Third month employment for Other services', 'Employment level for the third month of a  given quarter for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (472, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1027', 'Numeric', 'Quarterly location quotient weekly wage for Other services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (473, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1027', 'Numeric', 'Location quotient for Other services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (474, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1027', 'Numeric', 'Location quotient third month for Other services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Other services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (475, NULL, NULL, '"us.bls".avg_wkly_wage_naics1028', 'Numeric', 'Average weekly wage for Public administration', 'Average weekly wage for a given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (476, NULL, NULL, '"us.bls".qtrly_estabs_naics1028', 'Numeric', 'Establishment count for Public administration', 'Count of establishments for a given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (477, NULL, NULL, '"us.bls".month3_emplvl_naics1028', 'Numeric', 'Third month employment for Public administration', 'Employment level for the third month of a  given quarter for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (478, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1028', 'Numeric', 'Quarterly location quotient weekly wage for Public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (537, NULL, NULL, '"us.bls".qtrly_estabs_naics51', 'Numeric', 'Establishment count for NAICS 51 Information', 'Count of establishments for a given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (479, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1028', 'Numeric', 'Location quotient for Public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (480, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1028', 'Numeric', 'Location quotient third month for Public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (481, NULL, NULL, '"us.bls".avg_wkly_wage_naics1029', 'Numeric', 'Average weekly wage for Unclassified', 'Average weekly wage for a given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (482, NULL, NULL, '"us.bls".qtrly_estabs_naics1029', 'Numeric', 'Establishment count for Unclassified', 'Count of establishments for a given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (483, NULL, NULL, '"us.bls".month3_emplvl_naics1029', 'Numeric', 'Third month employment for Unclassified', 'Employment level for the third month of a  given quarter for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (484, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics1029', 'Numeric', 'Quarterly location quotient weekly wage for Unclassified', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (485, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics1029', 'Numeric', 'Location quotient for Unclassified', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (486, NULL, NULL, '"us.bls".lq_month3_emplvl_naics1029', 'Numeric', 'Location quotient third month for Unclassified', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (487, NULL, NULL, '"us.bls".avg_wkly_wage_naics11', 'Numeric', 'Average weekly wage for NAICS 11 Agriculture, forestry, fishing and hunting', 'Average weekly wage for a given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (488, NULL, NULL, '"us.bls".qtrly_estabs_naics11', 'Numeric', 'Establishment count for NAICS 11 Agriculture, forestry, fishing and hunting', 'Count of establishments for a given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (489, NULL, NULL, '"us.bls".month3_emplvl_naics11', 'Numeric', 'Third month employment for NAICS 11 Agriculture, forestry, fishing and hunting', 'Employment level for the third month of a  given quarter for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (490, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics11', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (491, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics11', 'Numeric', 'Location quotient for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (492, NULL, NULL, '"us.bls".lq_month3_emplvl_naics11', 'Numeric', 'Location quotient third month for NAICS 11 Agriculture, forestry, fishing and hunting', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 11 Agriculture, forestry, fishing and hunting', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (493, NULL, NULL, '"us.bls".avg_wkly_wage_naics21', 'Numeric', 'Average weekly wage for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Average weekly wage for a given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (494, NULL, NULL, '"us.bls".qtrly_estabs_naics21', 'Numeric', 'Establishment count for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Count of establishments for a given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (495, NULL, NULL, '"us.bls".month3_emplvl_naics21', 'Numeric', 'Third month employment for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Employment level for the third month of a  given quarter for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (496, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics21', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (497, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics21', 'Numeric', 'Location quotient for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (498, NULL, NULL, '"us.bls".lq_month3_emplvl_naics21', 'Numeric', 'Location quotient third month for NAICS 21 Mining, quarrying, and oil and gas extraction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 21 Mining, quarrying, and oil and gas extraction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (499, NULL, NULL, '"us.bls".avg_wkly_wage_naics22', 'Numeric', 'Average weekly wage for NAICS 22 Utilities', 'Average weekly wage for a given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (500, NULL, NULL, '"us.bls".qtrly_estabs_naics22', 'Numeric', 'Establishment count for NAICS 22 Utilities', 'Count of establishments for a given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (501, NULL, NULL, '"us.bls".month3_emplvl_naics22', 'Numeric', 'Third month employment for NAICS 22 Utilities', 'Employment level for the third month of a  given quarter for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (502, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics22', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 22 Utilities', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (503, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics22', 'Numeric', 'Location quotient for NAICS 22 Utilities', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (504, NULL, NULL, '"us.bls".lq_month3_emplvl_naics22', 'Numeric', 'Location quotient third month for NAICS 22 Utilities', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 22 Utilities', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (505, NULL, NULL, '"us.bls".avg_wkly_wage_naics23', 'Numeric', 'Average weekly wage for NAICS 23 Construction', 'Average weekly wage for a given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (506, NULL, NULL, '"us.bls".qtrly_estabs_naics23', 'Numeric', 'Establishment count for NAICS 23 Construction', 'Count of establishments for a given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (507, NULL, NULL, '"us.bls".month3_emplvl_naics23', 'Numeric', 'Third month employment for NAICS 23 Construction', 'Employment level for the third month of a  given quarter for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (508, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics23', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 23 Construction', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (509, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics23', 'Numeric', 'Location quotient for NAICS 23 Construction', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (510, NULL, NULL, '"us.bls".lq_month3_emplvl_naics23', 'Numeric', 'Location quotient third month for NAICS 23 Construction', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 23 Construction', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (511, NULL, NULL, '"us.bls".avg_wkly_wage_naics31_33', 'Numeric', 'Average weekly wage for NAICS 31-33 Manufacturing', 'Average weekly wage for a given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (512, NULL, NULL, '"us.bls".qtrly_estabs_naics31_33', 'Numeric', 'Establishment count for NAICS 31-33 Manufacturing', 'Count of establishments for a given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (513, NULL, NULL, '"us.bls".month3_emplvl_naics31_33', 'Numeric', 'Third month employment for NAICS 31-33 Manufacturing', 'Employment level for the third month of a  given quarter for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (514, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics31_33', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 31-33 Manufacturing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (515, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics31_33', 'Numeric', 'Location quotient for NAICS 31-33 Manufacturing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (516, NULL, NULL, '"us.bls".lq_month3_emplvl_naics31_33', 'Numeric', 'Location quotient third month for NAICS 31-33 Manufacturing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 31-33 Manufacturing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (517, NULL, NULL, '"us.bls".avg_wkly_wage_naics42', 'Numeric', 'Average weekly wage for NAICS 42 Wholesale trade', 'Average weekly wage for a given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (518, NULL, NULL, '"us.bls".qtrly_estabs_naics42', 'Numeric', 'Establishment count for NAICS 42 Wholesale trade', 'Count of establishments for a given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (519, NULL, NULL, '"us.bls".month3_emplvl_naics42', 'Numeric', 'Third month employment for NAICS 42 Wholesale trade', 'Employment level for the third month of a  given quarter for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (520, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics42', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 42 Wholesale trade', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (521, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics42', 'Numeric', 'Location quotient for NAICS 42 Wholesale trade', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (522, NULL, NULL, '"us.bls".lq_month3_emplvl_naics42', 'Numeric', 'Location quotient third month for NAICS 42 Wholesale trade', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 42 Wholesale trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (523, NULL, NULL, '"us.bls".avg_wkly_wage_naics44_45', 'Numeric', 'Average weekly wage for NAICS 44-45 Retail trade', 'Average weekly wage for a given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (524, NULL, NULL, '"us.bls".qtrly_estabs_naics44_45', 'Numeric', 'Establishment count for NAICS 44-45 Retail trade', 'Count of establishments for a given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (525, NULL, NULL, '"us.bls".month3_emplvl_naics44_45', 'Numeric', 'Third month employment for NAICS 44-45 Retail trade', 'Employment level for the third month of a  given quarter for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (526, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics44_45', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 44-45 Retail trade', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (527, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics44_45', 'Numeric', 'Location quotient for NAICS 44-45 Retail trade', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (528, NULL, NULL, '"us.bls".lq_month3_emplvl_naics44_45', 'Numeric', 'Location quotient third month for NAICS 44-45 Retail trade', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 44-45 Retail trade', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (529, NULL, NULL, '"us.bls".avg_wkly_wage_naics48_49', 'Numeric', 'Average weekly wage for NAICS 48-49 Transportation and warehousing', 'Average weekly wage for a given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (530, NULL, NULL, '"us.bls".qtrly_estabs_naics48_49', 'Numeric', 'Establishment count for NAICS 48-49 Transportation and warehousing', 'Count of establishments for a given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (531, NULL, NULL, '"us.bls".month3_emplvl_naics48_49', 'Numeric', 'Third month employment for NAICS 48-49 Transportation and warehousing', 'Employment level for the third month of a  given quarter for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (532, NULL, NULL, '"us.bls".month3_emplvl_naics55', 'Numeric', 'Third month employment for NAICS 55 Management of companies and enterprises', 'Employment level for the third month of a  given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (533, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics48_49', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 48-49 Transportation and warehousing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (534, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics48_49', 'Numeric', 'Location quotient for NAICS 48-49 Transportation and warehousing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (535, NULL, NULL, '"us.bls".lq_month3_emplvl_naics48_49', 'Numeric', 'Location quotient third month for NAICS 48-49 Transportation and warehousing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 48-49 Transportation and warehousing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (536, NULL, NULL, '"us.bls".avg_wkly_wage_naics51', 'Numeric', 'Average weekly wage for NAICS 51 Information', 'Average weekly wage for a given quarter for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (539, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics51', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 51 Information', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (540, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics51', 'Numeric', 'Location quotient for NAICS 51 Information', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (541, NULL, NULL, '"us.bls".lq_month3_emplvl_naics51', 'Numeric', 'Location quotient third month for NAICS 51 Information', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 51 Information', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (542, NULL, NULL, '"us.bls".avg_wkly_wage_naics52', 'Numeric', 'Average weekly wage for NAICS 52 Finance and insurance', 'Average weekly wage for a given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (543, NULL, NULL, '"us.bls".qtrly_estabs_naics52', 'Numeric', 'Establishment count for NAICS 52 Finance and insurance', 'Count of establishments for a given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (544, NULL, NULL, '"us.bls".month3_emplvl_naics52', 'Numeric', 'Third month employment for NAICS 52 Finance and insurance', 'Employment level for the third month of a  given quarter for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (545, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics52', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 52 Finance and insurance', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (546, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics52', 'Numeric', 'Location quotient for NAICS 52 Finance and insurance', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (547, NULL, NULL, '"us.bls".lq_month3_emplvl_naics52', 'Numeric', 'Location quotient third month for NAICS 52 Finance and insurance', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 52 Finance and insurance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (548, NULL, NULL, '"us.bls".avg_wkly_wage_naics53', 'Numeric', 'Average weekly wage for NAICS 53 Real estate and rental and leasing', 'Average weekly wage for a given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (549, NULL, NULL, '"us.bls".qtrly_estabs_naics53', 'Numeric', 'Establishment count for NAICS 53 Real estate and rental and leasing', 'Count of establishments for a given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (550, NULL, NULL, '"us.bls".month3_emplvl_naics53', 'Numeric', 'Third month employment for NAICS 53 Real estate and rental and leasing', 'Employment level for the third month of a  given quarter for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (551, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics53', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 53 Real estate and rental and leasing', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (552, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics53', 'Numeric', 'Location quotient for NAICS 53 Real estate and rental and leasing', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (553, NULL, NULL, '"us.bls".lq_month3_emplvl_naics53', 'Numeric', 'Location quotient third month for NAICS 53 Real estate and rental and leasing', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 53 Real estate and rental and leasing', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (554, NULL, NULL, '"us.bls".avg_wkly_wage_naics54', 'Numeric', 'Average weekly wage for NAICS 54 Professional and technical services', 'Average weekly wage for a given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (555, NULL, NULL, '"us.bls".qtrly_estabs_naics54', 'Numeric', 'Establishment count for NAICS 54 Professional and technical services', 'Count of establishments for a given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (556, NULL, NULL, '"us.bls".month3_emplvl_naics54', 'Numeric', 'Third month employment for NAICS 54 Professional and technical services', 'Employment level for the third month of a  given quarter for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (557, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics54', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 54 Professional and technical services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (558, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics54', 'Numeric', 'Location quotient for NAICS 54 Professional and technical services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (559, NULL, NULL, '"us.bls".lq_month3_emplvl_naics54', 'Numeric', 'Location quotient third month for NAICS 54 Professional and technical services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 54 Professional and technical services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (560, NULL, NULL, '"us.bls".avg_wkly_wage_naics55', 'Numeric', 'Average weekly wage for NAICS 55 Management of companies and enterprises', 'Average weekly wage for a given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (561, NULL, NULL, '"us.bls".qtrly_estabs_naics55', 'Numeric', 'Establishment count for NAICS 55 Management of companies and enterprises', 'Count of establishments for a given quarter for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (617, NULL, NULL, '"us.census.acs".B03002002', 'Numeric', 'Population not Hispanic', 'The number of people not identifying as Hispanic or Latino in each geography.', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (562, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics55', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 55 Management of companies and enterprises', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (563, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics55', 'Numeric', 'Location quotient for NAICS 55 Management of companies and enterprises', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (564, NULL, NULL, '"us.bls".lq_month3_emplvl_naics55', 'Numeric', 'Location quotient third month for NAICS 55 Management of companies and enterprises', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 55 Management of companies and enterprises', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (565, NULL, NULL, '"us.bls".avg_wkly_wage_naics56', 'Numeric', 'Average weekly wage for NAICS 56 Administrative and waste services', 'Average weekly wage for a given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (566, NULL, NULL, '"us.bls".qtrly_estabs_naics56', 'Numeric', 'Establishment count for NAICS 56 Administrative and waste services', 'Count of establishments for a given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (567, NULL, NULL, '"us.bls".month3_emplvl_naics56', 'Numeric', 'Third month employment for NAICS 56 Administrative and waste services', 'Employment level for the third month of a  given quarter for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (568, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics56', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 56 Administrative and waste services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (569, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics56', 'Numeric', 'Location quotient for NAICS 56 Administrative and waste services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (570, NULL, NULL, '"us.bls".lq_month3_emplvl_naics56', 'Numeric', 'Location quotient third month for NAICS 56 Administrative and waste services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 56 Administrative and waste services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (571, NULL, NULL, '"us.bls".avg_wkly_wage_naics61', 'Numeric', 'Average weekly wage for NAICS 61 Educational services', 'Average weekly wage for a given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (572, NULL, NULL, '"us.bls".qtrly_estabs_naics61', 'Numeric', 'Establishment count for NAICS 61 Educational services', 'Count of establishments for a given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (573, NULL, NULL, '"us.bls".month3_emplvl_naics61', 'Numeric', 'Third month employment for NAICS 61 Educational services', 'Employment level for the third month of a  given quarter for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (574, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics61', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 61 Educational services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (575, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics61', 'Numeric', 'Location quotient for NAICS 61 Educational services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (576, NULL, NULL, '"us.bls".lq_month3_emplvl_naics61', 'Numeric', 'Location quotient third month for NAICS 61 Educational services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 61 Educational services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (577, NULL, NULL, '"us.bls".avg_wkly_wage_naics62', 'Numeric', 'Average weekly wage for NAICS 62 Health care and social assistance', 'Average weekly wage for a given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (578, NULL, NULL, '"us.bls".qtrly_estabs_naics62', 'Numeric', 'Establishment count for NAICS 62 Health care and social assistance', 'Count of establishments for a given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (579, NULL, NULL, '"us.bls".month3_emplvl_naics62', 'Numeric', 'Third month employment for NAICS 62 Health care and social assistance', 'Employment level for the third month of a  given quarter for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (580, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics62', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 62 Health care and social assistance', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (581, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics62', 'Numeric', 'Location quotient for NAICS 62 Health care and social assistance', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (582, NULL, NULL, '"us.bls".lq_month3_emplvl_naics62', 'Numeric', 'Location quotient third month for NAICS 62 Health care and social assistance', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 62 Health care and social assistance', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (583, NULL, NULL, '"us.bls".avg_wkly_wage_naics71', 'Numeric', 'Average weekly wage for NAICS 71 Arts, entertainment, and recreation', 'Average weekly wage for a given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (584, NULL, NULL, '"us.bls".qtrly_estabs_naics71', 'Numeric', 'Establishment count for NAICS 71 Arts, entertainment, and recreation', 'Count of establishments for a given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (585, NULL, NULL, '"us.bls".month3_emplvl_naics71', 'Numeric', 'Third month employment for NAICS 71 Arts, entertainment, and recreation', 'Employment level for the third month of a  given quarter for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (586, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics71', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (587, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics71', 'Numeric', 'Location quotient for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (649, NULL, NULL, '"us.census.acs".B19001005', 'Numeric', 'Households with income of $20,000 To $24,999', 'The number of households in a geographic area whose annual income was between $20,000 and $24,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (588, NULL, NULL, '"us.bls".lq_month3_emplvl_naics71', 'Numeric', 'Location quotient third month for NAICS 71 Arts, entertainment, and recreation', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 71 Arts, entertainment, and recreation', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (589, NULL, NULL, '"us.bls".avg_wkly_wage_naics72', 'Numeric', 'Average weekly wage for NAICS 72 Accommodation and food services', 'Average weekly wage for a given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (591, NULL, NULL, '"us.bls".qtrly_estabs_naics72', 'Numeric', 'Establishment count for NAICS 72 Accommodation and food services', 'Count of establishments for a given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (654, NULL, NULL, '"us.census.acs".B19001010', 'Numeric', 'Households with income of $45,000 To $49,999', 'The number of households in a geographic area whose annual income was between $45,000 and $49,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (592, NULL, NULL, '"us.bls".month3_emplvl_naics72', 'Numeric', 'Third month employment for NAICS 72 Accommodation and food services', 'Employment level for the third month of a  given quarter for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (593, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics72', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 72 Accommodation and food services', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (594, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics72', 'Numeric', 'Location quotient for NAICS 72 Accommodation and food services', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (595, NULL, NULL, '"us.bls".lq_month3_emplvl_naics72', 'Numeric', 'Location quotient third month for NAICS 72 Accommodation and food services', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 72 Accommodation and food services', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (596, NULL, NULL, '"us.bls".avg_wkly_wage_naics81', 'Numeric', 'Average weekly wage for NAICS 81 Other services, except public administration', 'Average weekly wage for a given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (597, NULL, NULL, '"us.bls".qtrly_estabs_naics81', 'Numeric', 'Establishment count for NAICS 81 Other services, except public administration', 'Count of establishments for a given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (598, NULL, NULL, '"us.bls".month3_emplvl_naics81', 'Numeric', 'Third month employment for NAICS 81 Other services, except public administration', 'Employment level for the third month of a  given quarter for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (599, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics81', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 81 Other services, except public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (600, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics81', 'Numeric', 'Location quotient for NAICS 81 Other services, except public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (601, NULL, NULL, '"us.bls".lq_month3_emplvl_naics81', 'Numeric', 'Location quotient third month for NAICS 81 Other services, except public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 81 Other services, except public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (602, NULL, NULL, '"us.bls".avg_wkly_wage_naics92', 'Numeric', 'Average weekly wage for NAICS 92 Public administration', 'Average weekly wage for a given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (603, NULL, NULL, '"us.bls".qtrly_estabs_naics92', 'Numeric', 'Establishment count for NAICS 92 Public administration', 'Count of establishments for a given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (604, NULL, NULL, '"us.bls".month3_emplvl_naics92', 'Numeric', 'Third month employment for NAICS 92 Public administration', 'Employment level for the third month of a  given quarter for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (605, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics92', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 92 Public administration', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (606, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics92', 'Numeric', 'Location quotient for NAICS 92 Public administration', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (607, NULL, NULL, '"us.bls".lq_month3_emplvl_naics92', 'Numeric', 'Location quotient third month for NAICS 92 Public administration', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 92 Public administration', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (608, NULL, NULL, '"us.bls".avg_wkly_wage_naics99', 'Numeric', 'Average weekly wage for NAICS 99 Unclassified', 'Average weekly wage for a given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (609, NULL, NULL, '"us.bls".qtrly_estabs_naics99', 'Numeric', 'Establishment count for NAICS 99 Unclassified', 'Count of establishments for a given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (610, NULL, NULL, '"us.bls".month3_emplvl_naics99', 'Numeric', 'Third month employment for NAICS 99 Unclassified', 'Employment level for the third month of a  given quarter for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (611, NULL, NULL, '"us.bls".lq_avg_wkly_wage_naics99', 'Numeric', 'Quarterly location quotient weekly wage for NAICS 99 Unclassified', 'Location quotient of the average weekly wage for a given quarter relative to the U.S. (Rounded to hundredths place) for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (612, NULL, NULL, '"us.bls".lq_qtrly_estabs_naics99', 'Numeric', 'Location quotient for NAICS 99 Unclassified', 'Location quotient of the quarterly establishment count relative to the U.S. (Rounded to hundredths place) for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (613, NULL, NULL, '"us.bls".lq_month3_emplvl_naics99', 'Numeric', 'Location quotient third month for NAICS 99 Unclassified', 'Location quotient of the employment level for the third month of a given quarter relative to the U.S. (Rounded to hundredths place)), for NAICS 99 Unclassified', 0, 'sum', 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (614, NULL, NULL, '"us.census.acs".B03002005', 'Numeric', 'American Indian and Alaska Native Population', 'The number of people identifying as American Indian or Alaska native in each geography.', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (615, NULL, NULL, '"us.census.acs".B03002008', 'Numeric', 'Other Race population', 'The number of people identifying as another race in each geography', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (616, NULL, NULL, '"us.census.acs".B03002009', 'Numeric', 'Two or more races population', 'The number of people identifying as two or more races in each geography', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (618, NULL, NULL, '"us.census.acs".B08006001', 'Numeric', 'Workers over the Age of 16', 'The number of people in each geography who work. Workers include those employed at private for-profit companies, the self-employed, government workers and non-profit employees.', 5, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (619, NULL, NULL, '"us.census.acs".B08006002', 'Numeric', 'Commuters by Car, Truck, or Van', 'The number of workers age 16 years and over within  a geographic area who primarily traveled to work by car, truck or  van.  This is the principal mode of travel or type of conveyance,  by distance rather than time, that the worker usually used to get  from home to work.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (655, NULL, NULL, '"us.census.acs".B19001011', 'Numeric', 'Households with income of $50,000 To $59,999', 'The number of households in a geographic area whose annual income was between $50,000 and $59,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (620, NULL, NULL, '"us.census.acs".B08006004', 'Numeric', 'Commuters by Carpool', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by carpool.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (621, NULL, NULL, '"us.census.acs".B08006003', 'Numeric', 'Commuters who drove alone', 'The number of workers age 16 years and over within a geographic area who primarily traveled by car driving alone. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (622, NULL, NULL, '"us.census.acs".B11001001', 'Numeric', 'Households', 'A count of the number of households in each geography. A household consists of one or more people who live in the same dwelling and also share at meals or living accommodation, and may consist of a single family or some other grouping of people. ', 8, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (623, NULL, NULL, '"us.census.acs".B19001017', 'Numeric', 'Households with income of $200,000 Or More', 'The number of households in a geographic area whose annual income was more than $200,000.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (624, NULL, NULL, '"us.census.acs".B15003019', 'Numeric', 'Population completed less than one year of college, no degree', 'The number of people in a geographic area over the age of 25 who attended college for less than one year and no further.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (625, NULL, NULL, '"us.census.acs".B15003020', 'Numeric', 'Population completed more than one year of college, no degree', 'The number of people in a geographic area over the age of 25 who attended college for more than one year but did not obtain a degree', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (626, NULL, NULL, '"us.census.acs".B15003021', 'Numeric', 'Population Completed Associate''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a associate''s degree, and did not complete a more advanced degree.', 4, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (627, NULL, NULL, '"us.census.acs".B23008010', 'Numeric', 'One-parent families, father in labor force, with young children (under 6 years of age)', '', 0, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (629, NULL, NULL, '"us.census.acs".B12005001', 'Numeric', 'Population 15 Years and Over', 'The number of people in a geographic area who are over the age of 15.  This is used mostly as a denominator of marital status.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (630, NULL, NULL, '"us.census.acs".B12005015', 'Numeric', 'Divorced', 'The number of people in a geographic area who are divorced', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (631, NULL, NULL, '"us.census.acs".B12005002', 'Numeric', 'Never Married', 'The number of people in a geographic area who have never been married.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (632, NULL, NULL, '"us.census.acs".B12005005', 'Numeric', 'Currently married', 'The number of people in a geographic area who are currently married', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (633, NULL, NULL, '"us.census.acs".B12005008', 'Numeric', 'Married but separated', 'The number of people in a geographic area who are married but separated', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (634, NULL, NULL, '"us.census.acs".B12005012', 'Numeric', 'Widowed', 'The number of people in a geographic area who are widowed', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (635, NULL, NULL, '"us.census.acs".B08134001', 'Numeric', 'Workers age 16 and over who do not work from home', 'The number of workers over the age of 16 who do not work from home in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (636, NULL, NULL, '"us.census.acs".B08135001', 'Numeric', 'Aggregate travel time to work', 'The total number of minutes every worker over the age of 16 who did not work from home spent spent commuting to work in one day in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (637, NULL, NULL, '"us.census.acs".B08134002', 'Numeric', 'Number of workers with less than 10 minute commute', 'The number of workers over the age of 16 who do not work from home and commute in less than 10 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (638, NULL, NULL, '"us.census.acs".B08134003', 'Numeric', 'Number of workers with a commute between 10 and 14 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 10 and 14 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (639, NULL, NULL, '"us.census.acs".B08134004', 'Numeric', 'Number of workers with a commute between 15 and 19 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 15 and 19 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (640, NULL, NULL, '"us.census.acs".B08134005', 'Numeric', 'Number of workers with a commute between 20 and 24 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 20 and 24 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (641, NULL, NULL, '"us.census.acs".B08134006', 'Numeric', 'Number of workers with a commute between 25 and 29 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 25 and 29 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (642, NULL, NULL, '"us.census.acs".B08134007', 'Numeric', 'Number of workers with a commute between 30 and 34 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 30 and 34 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (643, NULL, NULL, '"us.census.acs".B08134008', 'Numeric', 'Number of workers with a commute between 35 and 44 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 35 and 44 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (644, NULL, NULL, '"us.census.acs".B08134009', 'Numeric', 'Number of workers with a commute between 45 and 59 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 45 and 59 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (645, NULL, NULL, '"us.census.acs".B08134010', 'Numeric', 'Number of workers with a commute of over 60 minutes', 'The number of workers over the age of 16 who do not work from home and commute in over 60 minutes in a geographic area', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (646, NULL, NULL, '"us.census.acs".B19001002', 'Numeric', 'Households with income less than $10,000', 'The number of households in a geographic area whose annual income was less than $10,000.', 2, 'sum', 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (647, NULL, NULL, '"us.census.acs".B19001003', 'Numeric', 'Households with income of $10,000 to $14,999', 'The number of households in a geographic area whose annual income was between $10,000 and $14,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (648, NULL, NULL, '"us.census.acs".B19001004', 'Numeric', 'Households with income of $15,000 to $19,999', 'The number of households in a geographic area whose annual income was between $15,000 and $19,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (650, NULL, NULL, '"us.census.acs".B19001006', 'Numeric', 'Households with income of $25,000 To $29,999', 'The number of households in a geographic area whose annual income was between $20,000 and $24,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (651, NULL, NULL, '"us.census.acs".B19001007', 'Numeric', 'Households with income of $30,000 To $34,999', 'The number of households in a geographic area whose annual income was between $30,000 and $34,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (652, NULL, NULL, '"us.census.acs".B19001008', 'Numeric', 'Households with income of $35,000 To $39,999', 'The number of households in a geographic area whose annual income was between $35,000 and $39,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (653, NULL, NULL, '"us.census.acs".B19001009', 'Numeric', 'Households with income of $40,000 To $44,999', 'The number of households in a geographic area whose annual income was between $40,000 and $44,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (656, NULL, NULL, '"us.census.acs".B19001012', 'Numeric', 'Households with income of $60,000 To $74,999', 'The number of households in a geographic area whose annual income was between $60,000 and $74,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (657, NULL, NULL, '"us.census.acs".B19001013', 'Numeric', 'Households with income of $75,000 To $99,999', 'The number of households in a geographic area whose annual income was between $75,000 and $99,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (658, NULL, NULL, '"us.census.acs".B19001014', 'Numeric', 'Households with income of $100,000 To $124,999', 'The number of households in a geographic area whose annual income was between $100,000 and $124,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (659, NULL, NULL, '"us.census.acs".B19001015', 'Numeric', 'Households with income of $125,000 To $149,999', 'The number of households in a geographic area whose annual income was between $125,000 and $149,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (660, NULL, NULL, '"us.census.acs".B19001016', 'Numeric', 'Households with income of $150,000 To $199,999', 'The number of households in a geographic area whose annual income was between $150,000 and $1999,999.', 2, NULL, 1, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (662, NULL, NULL, '"us.ny.nyc.opendata".good_through_date', 'Date', 'Good Through Date', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (663, NULL, NULL, '"us.ny.nyc.opendata".record_type', 'Text', 'Record Type', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (664, NULL, NULL, '"us.ny.nyc.opendata"."us.ny.nyc.opendata".document_id', 'Text', 'Document ID', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (665, NULL, NULL, '"us.ny.nyc.opendata"."us.ny.nyc.opendata".record_type', 'Text', 'Record Type', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (666, NULL, NULL, '"us.ny.nyc.opendata".block', 'Integer', 'Block', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (667, NULL, NULL, '"us.ny.nyc.opendata".lot', 'Integer', 'Lot', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (668, NULL, NULL, '"us.ny.nyc.opendata".easement', 'Text', 'Easement', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (669, NULL, NULL, '"us.ny.nyc.opendata".partial_lot', 'Text', 'Partial Lot', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (670, NULL, NULL, '"us.ny.nyc.opendata".air_rights', 'Text', 'Air Rights', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (671, NULL, NULL, '"us.ny.nyc.opendata".subterranean_rights', 'Text', 'Subterranean Rights', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (672, NULL, NULL, '"us.ny.nyc.opendata".property_type', 'Text', 'Property Type', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (673, NULL, NULL, '"us.ny.nyc.opendata".street_number', 'Text', 'Street Number', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (674, NULL, NULL, '"us.ny.nyc.opendata".street_name', 'Text', 'Street Name', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (675, NULL, NULL, '"us.ny.nyc.opendata".unit', 'Text', 'Unit', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (676, NULL, NULL, '"us.ny.nyc.opendata"."us.ny.nyc.opendata".good_through_date', 'Date', 'Good Through Date', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (677, NULL, NULL, '"us.census.spielman_singleton_segments".X10', 'Text', 'SS_segment_10_clusters', 'Sociodemographic classes from Spielman and Singleton 2015, 10 clusters', 0, NULL, 3, '{"categories": {"Hispanic and Young": "Hispanic and Young description", "Wealthy Nuclear Families": "Wealthy Nuclear Families desc", "Middle Income, Single Family Home": "Middle Income, Single Family Home desc", "Native American": "Native American desc", "Wealthy, urban without Kids": "Wealthy, urban without Kids desc", "Low income and diverse": "Low income and diverse desc", "Wealthy Old Caucasion": "Wealthy Old Caucasion desc", "Low income, mix of minorities": "Low income, mix of minorities desc", "Low income, African American": "Low income, African American desc", "Residential Institutions": "Residential Institutions desc"}}');
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (678, NULL, NULL, '"us.census.spielman_singleton_segments".X2', 'Text', 'SS_segment_2_clusters', 'Sociodemographic classes from Spielman and Singleton 2015, 10 clusters', 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (679, NULL, NULL, '"us.ny.nyc.opendata".crfn', 'Text', 'City Reel File Number', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (680, NULL, NULL, '"us.ny.nyc.opendata".borough', 'Text', 'borough', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (681, NULL, NULL, '"us.ny.nyc.opendata".doc_type', 'Text', 'Document Type', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (682, NULL, NULL, '"us.ny.nyc.opendata".doc_date', 'Text', 'Document Date', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (683, NULL, NULL, '"us.ny.nyc.opendata".doc_amt', 'Text', 'Document Amount', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (684, NULL, NULL, '"us.ny.nyc.opendata".recorded_filed', 'Text', 'Recorded / Filed', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (685, NULL, NULL, '"us.ny.nyc.opendata".modified_date', 'Date', 'Modified Date', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (686, NULL, NULL, '"us.ny.nyc.opendata".reel_year', 'Integer', 'Reel Year', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (687, NULL, NULL, '"us.ny.nyc.opendata".reel_nbr', 'Text', 'Reel Number', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (688, NULL, NULL, '"us.ny.nyc.opendata".reel_page', 'Text', 'Reel Pgae', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (689, NULL, NULL, '"us.ny.nyc.opendata".percent_transferred', 'Text', 'precent_transferred', NULL, 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (690, NULL, NULL, '"us.ny.nyc.opendata".party_type', 'Integer', 'Party Type', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (691, NULL, NULL, '"us.ny.nyc.opendata".name', 'Text', 'Name', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (692, NULL, NULL, '"us.ny.nyc.opendata".address1', 'Text', 'Address 1', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (693, NULL, NULL, '"us.ny.nyc.opendata".address2', 'Text', 'Address 2', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (694, NULL, NULL, '"us.ny.nyc.opendata".country', 'Text', 'country', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (695, NULL, NULL, '"us.ny.nyc.opendata".city', 'Text', 'city', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (696, NULL, NULL, '"us.ny.nyc.opendata".state', 'Text', 'state', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (697, NULL, NULL, '"us.ny.nyc.opendata".zip', 'Text', 'zip', NULL, 0, NULL, 0, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (698, NULL, NULL, '"us.census.spielman_singleton_segments".X31', 'Text', 'SS_segment_31_clusters', 'Sociodemographic classes from Spielman and Singleton 2015, 10 clusters', 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (699, NULL, NULL, '"us.census.spielman_singleton_segments".X55', 'Text', 'SS_segment_55_clusters', 'Sociodemographic classes from Spielman and Singleton 2015, 10 clusters', 0, NULL, 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (700, NULL, NULL, '"us.census.acs".B01001001_quantile', 'Numeric', 'Quantile:Total Population', 'The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (702, NULL, NULL, '"us.census.acs".B01001026_quantile', 'Numeric', 'Quantile:Female Population', 'The number of people within each geography who are female.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (703, NULL, NULL, '"us.census.acs".B01002001_quantile', 'Numeric', 'Quantile:Median Age', 'The median age of all people in a given geographic area.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (704, NULL, NULL, '"us.census.acs".B03002003_quantile', 'Numeric', 'Quantile:White Population', 'The number of people identifying as white, non-Hispanic in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (705, NULL, NULL, '"us.census.acs".B03002004_quantile', 'Numeric', 'Quantile:Black or African American Population', 'The number of people identifying as black or African American, non-Hispanic in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (706, NULL, NULL, '"us.census.acs".B03002006_quantile', 'Numeric', 'Quantile:Asian Population', 'The number of people identifying as Asian, non-Hispanic in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (707, NULL, NULL, '"us.census.acs".B03002012_quantile', 'Numeric', 'Quantile:Hispanic Population', 'The number of people identifying as Hispanic or Latino in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (708, NULL, NULL, '"us.census.acs".B03002005_quantile', 'Numeric', 'Quantile:American Indian and Alaska Native Population', 'The number of people identifying as American Indian or Alaska native in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (709, NULL, NULL, '"us.census.acs".B03002008_quantile', 'Numeric', 'Quantile:Other Race population', 'The number of people identifying as another race in each geography', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (710, NULL, NULL, '"us.census.acs".B03002009_quantile', 'Numeric', 'Quantile:Two or more races population', 'The number of people identifying as two or more races in each geography', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (711, NULL, NULL, '"us.census.acs".B03002002_quantile', 'Numeric', 'Quantile:Population not Hispanic', 'The number of people not identifying as Hispanic or Latino in each geography.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (712, NULL, NULL, '"us.census.acs".B05001006_quantile', 'Numeric', 'Quantile:Not a U.S. Citizen Population', 'The number of people within each geography who indicated that they are not U.S. citizens.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (713, NULL, NULL, '"us.census.acs".B08006001_quantile', 'Numeric', 'Quantile:Workers over the Age of 16', 'The number of people in each geography who work. Workers include those employed at private for-profit companies, the self-employed, government workers and non-profit employees.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (714, NULL, NULL, '"us.census.acs".B08006002_quantile', 'Numeric', 'Quantile:Commuters by Car, Truck, or Van', 'The number of workers age 16 years and over within  a geographic area who primarily traveled to work by car, truck or  van.  This is the principal mode of travel or type of conveyance,  by distance rather than time, that the worker usually used to get  from home to work.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (715, NULL, NULL, '"us.census.acs".B08006003_quantile', 'Numeric', 'Quantile:Commuters who drove alone', 'The number of workers age 16 years and over within a geographic area who primarily traveled by car driving alone. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (716, NULL, NULL, '"us.census.acs".B08006004_quantile', 'Numeric', 'Quantile:Commuters by Carpool', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by carpool.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (717, NULL, NULL, '"us.census.acs".B08006008_quantile', 'Numeric', 'Quantile:Commuters by Public Transportation', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by public transportation.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (718, NULL, NULL, '"us.census.acs".B08006009_quantile', 'Numeric', 'Quantile:Commuters by Bus', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by bus.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (719, NULL, NULL, '"us.census.acs".B08006011_quantile', 'Numeric', 'Quantile:Commuters by Subway or Elevated', 'The number of workers age 16 years and over within a geographic area who primarily traveled to work by subway or elevated train.  This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work.  This is a subset of workers who commuted by public transport.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (720, NULL, NULL, '"us.census.acs".B08006015_quantile', 'Numeric', 'Quantile:Walked to Work', 'The number of workers age 16 years and over within a geographic area who primarily walked to work.  This would mean that of any way of getting to work, they travelled the most distance walking.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (721, NULL, NULL, '"us.census.acs".B08006017_quantile', 'Numeric', 'Quantile:Worked at Home', 'The count within a geographical area of workers over the age of 16 who worked at home.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (722, NULL, NULL, '"us.census.acs".B09001001_quantile', 'Numeric', 'Quantile:children under 18 Years of Age', 'The number of people within each geography who are under 18 years of age.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (723, NULL, NULL, '"us.census.acs".B11001001_quantile', 'Numeric', 'Quantile:Households', 'A count of the number of households in each geography. A household consists of one or more people who live in the same dwelling and also share at meals or living accommodation, and may consist of a single family or some other grouping of people. ', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (724, NULL, NULL, '"us.census.acs".B14001001_quantile', 'Numeric', 'Quantile:Population 3 Years and Over', 'The total number of people in each geography age 3 years and over.  This denominator is mostly used to calculate rates of school enrollment.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (725, NULL, NULL, '"us.census.acs".B14001002_quantile', 'Numeric', 'Quantile:Students Enrolled in School', 'The total number of people in each geography currently enrolled at any level of school, from nursery or pre-school to advanced post-graduate education.  Only includes those over the age of 3.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (726, NULL, NULL, '"us.census.acs".B14001005_quantile', 'Numeric', 'Quantile:Students Enrolled in Grades 1 to 4', 'The total number of people in each geography currently enrolled in grades 1 through 4 inclusive.  This corresponds roughly to elementary school.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (727, NULL, NULL, '"us.census.acs".B14001006_quantile', 'Numeric', 'Quantile:Students Enrolled in Grades 5 to 8', 'The total number of people in each geography currently enrolled in grades 5 through 8 inclusive.  This corresponds roughly to middle school.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (728, NULL, NULL, '"us.census.acs".B14001007_quantile', 'Numeric', 'Quantile:Students Enrolled in Grades 9 to 12', 'The total number of people in each geography currently enrolled in grades 9 through 12 inclusive.  This corresponds roughly to high school.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (729, NULL, NULL, '"us.census.acs".B14001008_quantile', 'Numeric', 'Quantile:Students Enrolled as Undergraduate in College', 'The number of people in a geographic area who are enrolled in college at the undergraduate level. Enrollment refers to being registered or listed as a student in an educational program leading to a college degree. This may be a public school or college, a private school or college.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (730, NULL, NULL, '"us.census.acs".B15003001_quantile', 'Numeric', 'Quantile:Population 25 Years and Over', 'The number of people in a geographic area who are over the age of 25.  This is used mostly as a denominator of educational attainment.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (731, NULL, NULL, '"us.census.acs".B15003017_quantile', 'Numeric', 'Quantile:Population Completed High School', 'The number of people in a geographic area over the age of 25 who completed high school, and did not complete a more advanced degree.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (732, NULL, NULL, '"us.census.acs".B15003019_quantile', 'Numeric', 'Quantile:Population completed less than one year of college, no degree', 'The number of people in a geographic area over the age of 25 who attended college for less than one year and no further.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (733, NULL, NULL, '"us.census.acs".B15003020_quantile', 'Numeric', 'Quantile:Population completed more than one year of college, no degree', 'The number of people in a geographic area over the age of 25 who attended college for more than one year but did not obtain a degree', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (734, NULL, NULL, '"us.census.acs".B15003021_quantile', 'Numeric', 'Quantile:Population Completed Associate''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a associate''s degree, and did not complete a more advanced degree.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (735, NULL, NULL, '"us.census.acs".B15003022_quantile', 'Numeric', 'Quantile:Population Completed Bachelor''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a bachelor''s degree, and did not complete a more advanced degree.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (736, NULL, NULL, '"us.census.acs".B15003023_quantile', 'Numeric', 'Quantile:Population Completed Master''s Degree', 'The number of people in a geographic area over the age of 25 who obtained a master''s degree, but did not complete a more advanced degree.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (737, NULL, NULL, '"us.census.acs".B16001001_quantile', 'Numeric', 'Quantile:Population 5 Years and Over', 'The number of people in a geographic area who are over the age of 5.  This is primarily used as a denominator of measures of language spoken at home.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (738, NULL, NULL, '"us.census.acs".B16001002_quantile', 'Numeric', 'Quantile:Speaks only English at Home', 'The number of people in a geographic area over age 5 who speak only English at home.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (739, NULL, NULL, '"us.census.acs".B16001003_quantile', 'Numeric', 'Quantile:Speaks Spanish at Home', 'The number of people in a geographic area over age 5 who speak Spanish at home, possibly in addition to other languages.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (740, NULL, NULL, '"us.census.acs".B17001001_quantile', 'Numeric', 'Quantile:Population for Whom Poverty Status Determined', 'The number of people in each geography who could be identified as either living in poverty or not.  This should be used as the denominator when calculating poverty rates, as it excludes people for whom it was not possible to determine poverty.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (741, NULL, NULL, '"us.census.acs".B17001002_quantile', 'Numeric', 'Quantile:Income In The Past 12 Months Below Poverty Level', 'The number of people in a geographic area who are part of a family (which could be just them as an individual) determined to be "in poverty" following the Office of Management and Budget''s Directive 14. (https://www.census.gov/hhes/povmeas/methodology/ombdir14.html)', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (742, NULL, NULL, '"us.census.acs".B19013001_quantile', 'Numeric', 'Quantile:Median Household Income in the past 12 Months', 'Within a geographic area, the median income received by every household on a regular basis before payments for personal income taxes, social security, union dues, medicare deductions, etc.  It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans'' (VA) payments, unemployment and/or worker''s compensation, child support, and alimony.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (743, NULL, NULL, '"us.census.acs".B19083001_quantile', 'Numeric', 'Quantile:Gini Index', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (744, NULL, NULL, '"us.census.acs".B19301001_quantile', 'Numeric', 'Quantile:Per Capita Income in the past 12 Months', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (745, NULL, NULL, '"us.census.acs".B25001001_quantile', 'Numeric', 'Quantile:Housing Units', 'A count of housing units in each geography.  A housing unit is a house, an apartment, a mobile home or trailer, a group of rooms, or a single room occupied as separate living quarters, or if vacant, intended for occupancy as separate living quarters.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (746, NULL, NULL, '"us.census.acs".B25002003_quantile', 'Numeric', 'Quantile:Vacant Housing Units', 'The count of vacant housing units in a geographic area. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (747, NULL, NULL, '"us.census.acs".B25004002_quantile', 'Numeric', 'Quantile:Vacant Housing Units for Rent', 'The count of vacant housing units in a geographic area that are for rent. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (748, NULL, NULL, '"us.census.acs".B25004004_quantile', 'Numeric', 'Quantile:Vacant Housing Units for Sale', 'The count of vacant housing units in a geographic area that are for sale. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (749, NULL, NULL, '"us.census.acs".B25058001_quantile', 'Numeric', 'Quantile:Median Rent', 'The median contract rent within a geographic area. The contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (750, NULL, NULL, '"us.census.acs".B08134004_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 15 and 19 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 15 and 19 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (751, NULL, NULL, '"us.census.acs".B25071001_quantile', 'Numeric', 'Quantile:Percent of Household Income Spent on Rent', 'Within a geographic area, the median percentage of household income which was spent on gross rent.  Gross rent is the amount of the contract rent plus the estimated average monthly cost of utilities (electricity, gas, water, sewer etc.) and fuels (oil, coal, wood, etc.) if these are paid by the renter.  Household income is the sum of the income of all people 15 years and older living in the household.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (753, NULL, NULL, '"us.census.acs".B25075025_quantile', 'Numeric', 'Quantile:Owner-occupied Housing Units valued at $1,000,000 or more.', 'The count of owner occupied housing units in a geographic area that are valued at $1,000,000 or more.  Value is the respondent''s estimate of how much the property (house and lot, mobile home and lot, or condominium unit) would sell for if it were for sale.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (795, NULL, NULL, '"us.census.acs".B08134006_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 25 and 29 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 25 and 29 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (754, NULL, NULL, '"us.census.acs".B25081002_quantile', 'Numeric', 'Quantile:Owner-occupied Housing Units with a Mortgage', 'The count of housing units within a geographic area that are mortagaged. "Mortgage" refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust, trust deed, contracts to purchase, land contracts, junior mortgages, and home equity loans.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (755, NULL, NULL, '"us.census.acs".B23008002_quantile', 'Numeric', 'Quantile:Families with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (756, NULL, NULL, '"us.census.acs".B23008003_quantile', 'Numeric', 'Quantile:Two-parent families with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (757, NULL, NULL, '"us.census.acs".B23008004_quantile', 'Numeric', 'Quantile:Two-parent families, both parents in labor force with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (758, NULL, NULL, '"us.census.acs".B23008005_quantile', 'Numeric', 'Quantile:Two-parent families, father only in labor force with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (759, NULL, NULL, '"us.census.acs".B23008006_quantile', 'Numeric', 'Quantile:Two-parent families, mother only in labor force with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (760, NULL, NULL, '"us.census.acs".B23008007_quantile', 'Numeric', 'Quantile:Two-parent families, neither parent in labor force with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (761, NULL, NULL, '"us.census.acs".B23008008_quantile', 'Numeric', 'Quantile:One-parent families with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (762, NULL, NULL, '"us.census.acs".B23008009_quantile', 'Numeric', 'Quantile:One-parent families, father, with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (763, NULL, NULL, '"us.census.acs".B15001027_quantile', 'Numeric', 'Quantile:Men age 45 to 64 ("middle aged")', '0', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (764, NULL, NULL, '"us.census.acs".B01001015_quantile', 'Numeric', 'Quantile:Men age 45 to 49', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (765, NULL, NULL, '"us.census.acs".B01001016_quantile', 'Numeric', 'Quantile:Men age 50 to 54', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (766, NULL, NULL, '"us.census.acs".B01001017_quantile', 'Numeric', 'Quantile:Men age 55 to 59', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (767, NULL, NULL, '"us.census.acs".B01001018_quantile', 'Numeric', 'Quantile:Men age 60 to 61', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (768, NULL, NULL, '"us.census.acs".B01001019_quantile', 'Numeric', 'Quantile:Men age 62 to 64', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (769, NULL, NULL, '"us.census.acs".B01001B012_quantile', 'Numeric', 'Quantile:Black Men age 45 to 54', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (770, NULL, NULL, '"us.census.acs".B01001B013_quantile', 'Numeric', 'Quantile:Black Men age 55 to 64', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (771, NULL, NULL, '"us.census.acs".B01001I012_quantile', 'Numeric', 'Quantile:Hispanic Men age 45 to 54', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (772, NULL, NULL, '"us.census.acs".B01001I013_quantile', 'Numeric', 'Quantile:Hispanic Men age 55 to 64', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (773, NULL, NULL, '"us.census.acs".B01001H012_quantile', 'Numeric', 'Quantile:White Men age 45 to 54', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (774, NULL, NULL, '"us.census.acs".B01001H013_quantile', 'Numeric', 'Quantile:White Men age 55 to 64', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (775, NULL, NULL, '"us.census.acs".B01001D012_quantile', 'Numeric', 'Quantile:Asian Men age 45 to 54', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (776, NULL, NULL, '"us.census.acs".B01001D013_quantile', 'Numeric', 'Quantile:Asian Men age 55 to 64', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (777, NULL, NULL, '"us.census.acs".B15001028_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who attained less than a 9th grade education', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (778, NULL, NULL, '"us.census.acs".B15001029_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who attained between 9th and 12th grade, no diploma', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (779, NULL, NULL, '"us.census.acs".B15001030_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who completed high school or obtained GED', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (780, NULL, NULL, '"us.census.acs".B15001031_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who completed some college, no degree', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (781, NULL, NULL, '"us.census.acs".B15001032_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who obtained an associate''s degree', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (782, NULL, NULL, '"us.census.acs".B15001033_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who obtained a bachelor''s degree', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (783, NULL, NULL, '"us.census.acs".B15001034_quantile', 'Numeric', 'Quantile:Men age 45 to 64 who obtained a graduate or professional degree', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (784, NULL, NULL, '"us.census.acs".B23008010_quantile', 'Numeric', 'Quantile:One-parent families, father in labor force, with young children (under 6 years of age)', '', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (785, NULL, NULL, '"us.census.acs".B12005001_quantile', 'Numeric', 'Quantile:Population 15 Years and Over', 'The number of people in a geographic area who are over the age of 15.  This is used mostly as a denominator of marital status.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (786, NULL, NULL, '"us.census.acs".B12005002_quantile', 'Numeric', 'Quantile:Never Married', 'The number of people in a geographic area who have never been married.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (787, NULL, NULL, '"us.census.acs".B12005005_quantile', 'Numeric', 'Quantile:Currently married', 'The number of people in a geographic area who are currently married', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (788, NULL, NULL, '"us.census.acs".B12005008_quantile', 'Numeric', 'Quantile:Married but separated', 'The number of people in a geographic area who are married but separated', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (789, NULL, NULL, '"us.census.acs".B12005012_quantile', 'Numeric', 'Quantile:Widowed', 'The number of people in a geographic area who are widowed', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (790, NULL, NULL, '"us.census.acs".B12005015_quantile', 'Numeric', 'Quantile:Divorced', 'The number of people in a geographic area who are divorced', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (791, NULL, NULL, '"us.census.acs".B08134001_quantile', 'Numeric', 'Quantile:Workers age 16 and over who do not work from home', 'The number of workers over the age of 16 who do not work from home in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (792, NULL, NULL, '"us.census.acs".B08134002_quantile', 'Numeric', 'Quantile:Number of workers with less than 10 minute commute', 'The number of workers over the age of 16 who do not work from home and commute in less than 10 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (793, NULL, NULL, '"us.census.acs".B08134003_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 10 and 14 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 10 and 14 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (794, NULL, NULL, '"us.census.acs".B08134005_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 20 and 24 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 20 and 24 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (796, NULL, NULL, '"us.census.acs".B08134007_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 30 and 34 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 30 and 34 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (797, NULL, NULL, '"us.census.acs".B08134008_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 35 and 44 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 35 and 44 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (798, NULL, NULL, '"us.census.acs".B08134009_quantile', 'Numeric', 'Quantile:Number of workers with a commute between 45 and 59 minutes', 'The number of workers over the age of 16 who do not work from home and commute in between 45 and 59 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (799, NULL, NULL, '"us.census.acs".B08134010_quantile', 'Numeric', 'Quantile:Number of workers with a commute of over 60 minutes', 'The number of workers over the age of 16 who do not work from home and commute in over 60 minutes in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (800, NULL, NULL, '"us.census.acs".B08135001_quantile', 'Numeric', 'Quantile:Aggregate travel time to work', 'The total number of minutes every worker over the age of 16 who did not work from home spent spent commuting to work in one day in a geographic area', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (801, NULL, NULL, '"us.census.acs".B19001002_quantile', 'Numeric', 'Quantile:Households with income less than $10,000', 'The number of households in a geographic area whose annual income was less than $10,000.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (802, NULL, NULL, '"us.census.acs".B19001003_quantile', 'Numeric', 'Quantile:Households with income of $10,000 to $14,999', 'The number of households in a geographic area whose annual income was between $10,000 and $14,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (803, NULL, NULL, '"us.census.acs".B19001004_quantile', 'Numeric', 'Quantile:Households with income of $15,000 to $19,999', 'The number of households in a geographic area whose annual income was between $15,000 and $19,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (804, NULL, NULL, '"us.census.acs".B19001005_quantile', 'Numeric', 'Quantile:Households with income of $20,000 To $24,999', 'The number of households in a geographic area whose annual income was between $20,000 and $24,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (805, NULL, NULL, '"us.census.acs".B19001006_quantile', 'Numeric', 'Quantile:Households with income of $25,000 To $29,999', 'The number of households in a geographic area whose annual income was between $20,000 and $24,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (806, NULL, NULL, '"us.census.acs".B19001007_quantile', 'Numeric', 'Quantile:Households with income of $30,000 To $34,999', 'The number of households in a geographic area whose annual income was between $30,000 and $34,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (807, NULL, NULL, '"us.census.acs".B19001008_quantile', 'Numeric', 'Quantile:Households with income of $35,000 To $39,999', 'The number of households in a geographic area whose annual income was between $35,000 and $39,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (808, NULL, NULL, '"us.census.acs".B19001009_quantile', 'Numeric', 'Quantile:Households with income of $40,000 To $44,999', 'The number of households in a geographic area whose annual income was between $40,000 and $44,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (809, NULL, NULL, '"us.census.acs".B19001010_quantile', 'Numeric', 'Quantile:Households with income of $45,000 To $49,999', 'The number of households in a geographic area whose annual income was between $45,000 and $49,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (810, NULL, NULL, '"us.census.acs".B19001011_quantile', 'Numeric', 'Quantile:Households with income of $50,000 To $59,999', 'The number of households in a geographic area whose annual income was between $50,000 and $59,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (811, NULL, NULL, '"us.census.acs".B19001012_quantile', 'Numeric', 'Quantile:Households with income of $60,000 To $74,999', 'The number of households in a geographic area whose annual income was between $60,000 and $74,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (812, NULL, NULL, '"us.census.acs".B19001013_quantile', 'Numeric', 'Quantile:Households with income of $75,000 To $99,999', 'The number of households in a geographic area whose annual income was between $75,000 and $99,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (813, NULL, NULL, '"us.census.acs".B19001014_quantile', 'Numeric', 'Quantile:Households with income of $100,000 To $124,999', 'The number of households in a geographic area whose annual income was between $100,000 and $124,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (814, NULL, NULL, '"us.census.acs".B19001015_quantile', 'Numeric', 'Quantile:Households with income of $125,000 To $149,999', 'The number of households in a geographic area whose annual income was between $125,000 and $149,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (815, NULL, NULL, '"us.census.acs".B19001016_quantile', 'Numeric', 'Quantile:Households with income of $150,000 To $199,999', 'The number of households in a geographic area whose annual income was between $150,000 and $1999,999.', 0, 'quantile', 3, NULL);
-INSERT INTO obs_column (cartodb_id, the_geom, the_geom_webmercator, id, type, name, description, weight, aggregate, version, extra) VALUES (816, NULL, NULL, '"us.census.acs".B19001017_quantile', 'Numeric', 'Quantile:Households with income of $200,000 Or More', 'The number of households in a geographic area whose annual income was more than $200,000.', 0, 'quantile', 3, NULL);
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_column SET SCHEMA observatory;

src/pg/test/fixtures/obs_column_to_column.sql

@@ -1,294 +0,0 @@
-
-CREATE TABLE obs_column_to_column(cartodb_id bigint, the_geom geometry, the_geom_webmercator geometry, source_id text, target_id text, reltype text);
-
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (1, NULL, NULL, '"es.ine".pop_100_more', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (2, NULL, NULL, '"es.ine".pop_0_4', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (3, NULL, NULL, '"es.ine".pop_5_9', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (4, NULL, NULL, '"es.ine".pop_10_14', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (5, NULL, NULL, '"es.ine".pop_15_19', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (6, NULL, NULL, '"es.ine".pop_20_24', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (7, NULL, NULL, '"es.ine".pop_25_29', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (8, NULL, NULL, '"es.ine".pop_30_34', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (9, NULL, NULL, '"es.ine".pop_35_39', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (10, NULL, NULL, '"es.ine".pop_40_44', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (11, NULL, NULL, '"es.ine".pop_45_49', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (12, NULL, NULL, '"es.ine".pop_50_54', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (13, NULL, NULL, '"es.ine".pop_55_59', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (14, NULL, NULL, '"es.ine".pop_60_64', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (15, NULL, NULL, '"es.ine".pop_65_69', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (16, NULL, NULL, '"es.ine".pop_70_74', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (17, NULL, NULL, '"es.ine".pop_75_79', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (18, NULL, NULL, '"es.ine".pop_80_84', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (19, NULL, NULL, '"es.ine".pop_85_89', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (20, NULL, NULL, '"es.ine".pop_90_94', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (21, NULL, NULL, '"es.ine".pop_95_99', '"es.ine".total_pop', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (22, NULL, NULL, '"us.census.lodes".jobs_firm_age_500_more_employees', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (23, NULL, NULL, '"us.census.lodes".jobs_age_29_or_younger', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (24, NULL, NULL, '"us.census.lodes".jobs_age_30_to_54', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (25, NULL, NULL, '"us.census.lodes".jobs_age_55_or_older', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (26, NULL, NULL, '"us.census.lodes".jobs_earning_15000_or_less', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (27, NULL, NULL, '"us.census.lodes".jobs_earning_15001_to_40000', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (28, NULL, NULL, '"us.census.lodes".jobs_earning_40001_or_more', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (29, NULL, NULL, '"us.census.lodes".jobs_11_agriculture_forestry_fishing', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (30, NULL, NULL, '"us.census.lodes".jobs_21_mining_quarrying_oil_gas', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (31, NULL, NULL, '"us.census.lodes".jobs_22_utilities', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (32, NULL, NULL, '"us.census.lodes".jobs_23_construction', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (33, NULL, NULL, '"us.census.lodes".jobs_31_33_manufacturing', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (34, NULL, NULL, '"us.census.lodes".jobs_42_wholesale_trade', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (35, NULL, NULL, '"us.census.lodes".jobs_44_45_retail_trade', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (36, NULL, NULL, '"us.census.lodes".jobs_48_49_transport_warehousing', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (37, NULL, NULL, '"us.census.lodes".jobs_51_information', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (38, NULL, NULL, '"us.census.lodes".jobs_52_finance_and_insurance', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (39, NULL, NULL, '"us.census.lodes".jobs_53_real_estate_rental_leasing', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (40, NULL, NULL, '"us.census.lodes".jobs_54_professional_scientific_tech_services', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (41, NULL, NULL, '"us.census.lodes".jobs_55_management_of_companies_enterprises', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (42, NULL, NULL, '"us.census.lodes".jobs_56_admin_support_waste_management', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (43, NULL, NULL, '"us.census.lodes".jobs_61_educational_services', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (44, NULL, NULL, '"us.census.lodes".jobs_62_healthcare_social_assistance', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (45, NULL, NULL, '"us.census.lodes".jobs_71_arts_entertainment_recreation', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (46, NULL, NULL, '"us.census.lodes".jobs_72_accommodation_and_food', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (47, NULL, NULL, '"us.census.lodes".jobs_81_other_services_except_public_admin', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (48, NULL, NULL, '"us.census.lodes".jobs_92_public_administration', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (49, NULL, NULL, '"us.census.lodes".jobs_white', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (50, NULL, NULL, '"us.census.lodes".jobs_black', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (51, NULL, NULL, '"us.census.lodes".jobs_asian', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (52, NULL, NULL, '"us.census.lodes".jobs_hispanic', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (53, NULL, NULL, '"us.census.lodes".jobs_less_than_high_school', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (54, NULL, NULL, '"us.census.lodes".jobs_high_school', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (55, NULL, NULL, '"us.census.lodes".jobs_some_college', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (56, NULL, NULL, '"us.census.lodes".jobs_bachelors_or_advanced', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (57, NULL, NULL, '"us.census.lodes".jobs_male', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (58, NULL, NULL, '"us.census.lodes".jobs_female', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (59, NULL, NULL, '"us.census.lodes".jobs_firm_age_0_1_years', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (60, NULL, NULL, '"us.census.lodes".jobs_firm_age_2_3_years', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (61, NULL, NULL, '"us.census.lodes".jobs_firm_age_4_5_years', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (62, NULL, NULL, '"us.census.lodes".jobs_firm_age_6_10_years', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (63, NULL, NULL, '"us.census.lodes".jobs_firm_age_11_more_years', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (64, NULL, NULL, '"us.census.lodes".jobs_firm_age_0_19_employees', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (65, NULL, NULL, '"us.census.lodes".jobs_firm_age_20_49_employees', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (66, NULL, NULL, '"us.census.lodes".jobs_firm_age_50_249_employees', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (67, NULL, NULL, '"us.census.lodes".jobs_firm_age_250_499_employees', '"us.census.lodes".total_jobs', 'denominator');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (68, NULL, NULL, '"us.census.tiger".census_tract_geoid', '"us.census.tiger".census_tract', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (69, NULL, NULL, '"us.census.tiger".county_geoid', '"us.census.tiger".county', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (70, NULL, NULL, '"us.census.tiger".congressional_district_geoid', '"us.census.tiger".congressional_district', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (71, NULL, NULL, '"us.census.tiger".block_geoid', '"us.census.tiger".block', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (72, NULL, NULL, '"us.census.tiger".zcta5_geoid', '"us.census.tiger".zcta5', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (73, NULL, NULL, '"us.census.tiger".puma_geoid', '"us.census.tiger".puma', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (74, NULL, NULL, '"us.census.tiger".state_geoid', '"us.census.tiger".state', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (75, NULL, NULL, '"us.census.tiger".block_group_geoid', '"us.census.tiger".block_group', 'geom_ref');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (76, NULL, NULL, '"us.census.acs".B01001002', '"us.census.acs".B01001001', 'denominator');
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-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (264, NULL, NULL, '"us.census.acs".B08134004_quantile', '"us.census.acs".B08134004', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (265, NULL, NULL, '"us.census.acs".B08134005_quantile', '"us.census.acs".B08134005', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (266, NULL, NULL, '"us.census.acs".B08134006_quantile', '"us.census.acs".B08134006', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (267, NULL, NULL, '"us.census.acs".B08134007_quantile', '"us.census.acs".B08134007', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (268, NULL, NULL, '"us.census.acs".B08134008_quantile', '"us.census.acs".B08134008', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (269, NULL, NULL, '"us.census.acs".B08134009_quantile', '"us.census.acs".B08134009', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (270, NULL, NULL, '"us.census.acs".B08134010_quantile', '"us.census.acs".B08134010', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (271, NULL, NULL, '"us.census.acs".B08135001_quantile', '"us.census.acs".B08135001', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (272, NULL, NULL, '"us.census.acs".B19001002_quantile', '"us.census.acs".B19001002', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (273, NULL, NULL, '"us.census.acs".B19001003_quantile', '"us.census.acs".B19001003', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (274, NULL, NULL, '"us.census.acs".B19001004_quantile', '"us.census.acs".B19001004', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (275, NULL, NULL, '"us.census.acs".B19001005_quantile', '"us.census.acs".B19001005', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (276, NULL, NULL, '"us.census.acs".B19001006_quantile', '"us.census.acs".B19001006', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (277, NULL, NULL, '"us.census.acs".B19001007_quantile', '"us.census.acs".B19001007', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (278, NULL, NULL, '"us.census.acs".B19001008_quantile', '"us.census.acs".B19001008', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (279, NULL, NULL, '"us.census.acs".B19001009_quantile', '"us.census.acs".B19001009', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (280, NULL, NULL, '"us.census.acs".B19001010_quantile', '"us.census.acs".B19001010', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (281, NULL, NULL, '"us.census.acs".B19001011_quantile', '"us.census.acs".B19001011', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (282, NULL, NULL, '"us.census.acs".B19001012_quantile', '"us.census.acs".B19001012', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (283, NULL, NULL, '"us.census.acs".B19001013_quantile', '"us.census.acs".B19001013', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (284, NULL, NULL, '"us.census.acs".B19001014_quantile', '"us.census.acs".B19001014', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (285, NULL, NULL, '"us.census.acs".B19001015_quantile', '"us.census.acs".B19001015', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (286, NULL, NULL, '"us.census.acs".B19001016_quantile', '"us.census.acs".B19001016', 'quantile_source');
-INSERT INTO obs_column_to_column (cartodb_id, the_geom, the_geom_webmercator, source_id, target_id, reltype) VALUES (287, NULL, NULL, '"us.census.acs".B19001017_quantile', '"us.census.acs".B19001017', 'quantile_source');
-
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_column_to_column SET SCHEMA observatory;

src/pg/test/fixtures/obs_table.sql

@@ -1,39 +0,0 @@
-CREATE TABLE obs_table(cartodb_id bigint, the_geom geometry, the_geom_webmercator geometry, id text, tablename text, timespan text, bounds text, description text, version text);
-
-
--- Commented out until somebody actually adds that fixture
---INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (1, NULL, NULL, '"us.census.spielman_singleton_segments".spielman_singleton_table_99914b932b', 'obs_65f29658e096ca1485bf683f65fdbc9f05ec3c5d', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (2, NULL, NULL, '"us.census.acs".extract_block_group_5yr_2013_69b156927c', 'obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb', '2009 - 2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (3, NULL, NULL, '"us.census.tiger".sum_level_false_block_group_2013_5c764f39d2', 'obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (4, NULL, NULL, '"us.census.tiger".sum_level_false_census_tract_2013_c489085a44', 'obs_a92e1111ad3177676471d66bb8036e6d057f271b', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (5, NULL, NULL, '"us.ny.nyc.opendata".acris_master_99914b932b', 'obs_811c938d1307530a3db53fc69f11a2499174d224', '1966 - present', 'BOX(0 0,0 0)', NULL, 0);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (6, NULL, NULL, '"us.census.tiger".sum_level_false_county_2013_66804ade17', 'obs_b0ef6dd68d5faddbf231fd7f02916b3d00ec43c4', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (7, NULL, NULL, '"us.census.tiger".sum_level_false_puma_2013_4a11a4ba96', 'obs_0008b162b516c295d7204c9ba043ab5dbc67c59c', '2013', 'BOX(-179.231086 13.182335,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (8, NULL, NULL, '"us.census.tiger".sum_level_true_state_2013_f1ab8fce27', 'obs_a20f5260b618a2fe2eb95fc1e23febe0db7db096', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (9, NULL, NULL, '"us.census.tiger".sum_level_true_county_2013_39133ea7a1', 'obs_23da37d4e66e9de2f525572967f8618bde99a8c0', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (10, NULL, NULL, '"us.census.tiger".sum_level_false_zcta5_2013_bf420fa8c1', 'obs_d483723c5cc76c107d9e0af279d1e7056df3c2be', '2013', 'BOX(-176.684744 -14.373765,145.830505 71.341324)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (11, NULL, NULL, '"us.census.tiger".sum_level_true_census_tract_2013_6a2cf9dee9', 'obs_d125aeef87aaa23287a40b454519ece22ee25acf', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (12, NULL, NULL, '"us.census.tiger".sum_level_true_block_group_2013_5ecb940395', 'obs_d610cb3225f282693b8d4dcd98d2c2e2078354c6', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (13, NULL, NULL, '"us.census.acs".extract_state_5yr_2013_c6cc7dd346', 'obs_92bdae84ae8d41fabca52500e4e1f55c394b696e', '2009 - 2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (14, NULL, NULL, '"us.census.acs".extract_puma_5yr_2013_e9f0d7bc6c', 'obs_a875390344c7e36b72a8d6a3d25ae0f2bb41eaee', '2009 - 2013', 'BOX(-179.231086 13.182335,179.859681 71.441059)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (15, NULL, NULL, '"us.census.acs".extract_county_5yr_2013_5d7844896c', 'obs_75edf4ed5271a95f13755e9d06b80740b2fde0ba', '2009 - 2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (16, NULL, NULL, '"us.census.acs".extract_zcta5_5yr_2013_dc39ebe0d5', 'obs_e99034a8fff4654142aed05d887f745a32cedc9f', '2009 - 2013', 'BOX(-176.684744 -14.373765,145.830505 71.341324)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (17, NULL, NULL, '"us.census.acs".extract_census_tract_5yr_2013_a0eee6bf1a', 'obs_ab038198aaab3f3cb055758638ee4de28ad70146', '2009 - 2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (18, NULL, NULL, '"us.bls".raw_qcew_2013_dd20d99063', 'obs_530081a407e8793b7fef6666ebc46db0fcc9db2c', '2013', 'BOX(0 0,0 0)', NULL, 0);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (19, NULL, NULL, '"us.bls".naics_99914b932b', 'obs_609c848c80950261032da680294bb1e3ddcf43b6', NULL, 'BOX(0 0,0 0)', NULL, 0);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (20, NULL, NULL, '"us.bls".simple_qcew_4_2013_94c2fc9ef1', 'obs_4560238b6b0050979ad151becc37c6eecfb7e6ad', '2013Q4', 'BOX(0 0,0 0)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (21, NULL, NULL, '"us.census.lodes".workplace_area_characteristics_2013_dd20d99063', 'obs_5bc83d67ea2863b1712078813a730eee753cf316', '2013', 'BOX(0 0,0 0)', NULL, 0);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (22, NULL, NULL, '"us.bls".qcew_4_2013_94c2fc9ef1', 'obs_5ed30fab78289e09c30cfd16981b8143ca8fdaa4', '2013Q4', 'BOX(0 0,0 0)', NULL, 1);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (23, NULL, NULL, '"us.ny.nyc.opendata".acris_legals_99914b932b', 'obs_fd0a697088f5ffcbe4641fb62ad6e2c74eed55d5', '', 'BOX(0 0,0 0)', NULL, 0);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (24, NULL, NULL, '"us.census.spielman_singleton_segments".create_spielman_singleton_table_99914b932b', 'obs_11ee8b82c877c073438bc935a91d3dfccef875d1', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 3);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (25, NULL, NULL, '"us.census.acs".quantiles_block_group_5yr_2013_69b156927c', 'obs_0932dc0392ca14a6b43e6e131943de9af2ee46b2', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (26, NULL, NULL, '"us.census.acs".quantiles_puma_5yr_2013_e9f0d7bc6c', 'obs_032792417d754aa7708d6ba716eb446904f12c46', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (27, NULL, NULL, '"us.census.acs".quantiles_census_tract_5yr_2013_a0eee6bf1a', 'obs_d34555209878e8c4b37cf0b2b3d072ff129ec470', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (28, NULL, NULL, '"us.census.tiger".sum_level_false_state_2013_0b919d8984', 'obs_f3f0912fe24bc0c976e837b5a116d0c803cc01ce', '2013', 'BOX(-179.231086 -14.601813,179.859681 71.441059)', NULL, 4);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (29, NULL, NULL, '"us.census.acs".quantiles_zcta5_5yr_2013_dc39ebe0d5', 'obs_a31255ed256a27d69a9ea777621ad218f6f1f030', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (30, NULL, NULL, '"us.census.acs".quantiles_state_5yr_2013_c6cc7dd346', 'obs_90e9293f578fab0bf2dabf5e387a57d9a2739a08', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-INSERT INTO obs_table (cartodb_id, the_geom, the_geom_webmercator, id, tablename, timespan, bounds, description, version) VALUES (31, NULL, NULL, '"us.census.acs".quantiles_county_5yr_2013_5d7844896c', 'obs_98cefd377c2ff17a2d60b9a6fe090af629073ec4', '2009 - 2013', 'BOX(0 0,0 0)', NULL, 5);
-
-CREATE SCHEMA IF NOT EXISTS observatory;
-ALTER TABLE obs_table SET SCHEMA observatory;

src/pg/test/sql/40_observatory_utility_test.sql

@@ -1,78 +1,78 @@
-\i test/sql/load_fixtures.sql
-
+\pset format unaligned
 \set ECHO all
+\i test/fixtures/load_fixtures.sql
 
 -- OBS_GeomTable
 -- get table with known geometry_id
 -- should give back a table like obs_{hex hash}
 SELECT
   cdb_observatory._OBS_GeomTable(
-    CDB_LatLng(40.7128,-74.0059),
-    '"us.census.tiger".census_tract'
-  );
+    ST_SetSRID(ST_Point(-74.0059, 40.7128), 4326),
+    'us.census.tiger.census_tract',
+    '2014'
+  ) = 'obs_fc050f0b8673cfe3c6aa1040f749eb40975691b7' As _obs_geomtable_with_returned_table;
 
 -- get null for unknown geometry_id
 -- should give back null
 SELECT
   cdb_observatory._OBS_GeomTable(
-    CDB_LatLng(40.7128,-74.0059),
-    '"us.census.tiger".nonexistant_id' -- not in catalog
-  );
+    ST_SetSRID(ST_Point(-74.0059, 40.7128), 4326),
+    'us.census.tiger.nonexistant_id' -- not in catalog
+  ) IS NULL _obs_geomtable_with_null_response;
 
 -- future test: give back nulls when geometry doesn't intersect
 -- SELECT
 --   cdb_observatory._OBS_GeomTable(
---     CDB_LatLng(0,0), -- should give back null since it's in the ocean?
---     '"us.census.tiger".census_tract'
+--     ST_SetSRID(ST_Point(0,0)), -- should give back null since it's in the ocean?
+--     'us.census.tiger.census_tract'
 --   );
 
--- OBS_GetColumnData
--- should give back:
---  colname   | tablename       | aggregate
--- -----------|-----------------|-----------
---  geoid     | obs_{hex table} | null
---  total_pop | obs_{hex table} | sum
+WITH result as (
 SELECT
-  (unnest(cdb_observatory._OBS_GetColumnData(
-    '"us.census.tiger".census_tract',
-    Array['"us.census.tiger".census_tract_geoid', '"us.census.acs".B01001001'],
-    '2009 - 2013'
-  ))).*
-ORDER BY colname, tablename ASC;
+  array_agg(a) expected from cdb_observatory._OBS_GetColumnData(
+    'us.census.tiger.census_tract',
+    Array['us.census.spielman_singleton_segments.X55', 'us.census.acs.B01003001'],
+         '2010 - 2014') a
+)
+select
+(expected)[1]::text  = '{"colname":"x55","tablename":"obs_65f29658e096ca1485bf683f65fdbc9f05ec3c5d","aggregate":null,"name":"Spielman-Singleton Segments: 55 Clusters","type":"Text","description":"Sociodemographic classes from Spielman and Singleton 2015, 55 clusters","boundary_id":"us.census.tiger.census_tract"}' as test_get_obs_column_with_geoid_and_census_1,
+(expected)[2]::text  = '{"colname":"total_pop","tablename":"obs_b393b5b88c6adda634b2071a8005b03c551b609a","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.","boundary_id":"us.census.tiger.census_tract"}' as test_get_obs_column_with_geoid_and_census_2
+from result;
 
 -- should be null-valued
+WITH result as (
 SELECT
-  (unnest(cdb_observatory._OBS_GetColumnData(
-    '"us.census.tiger".census_tract',
-    Array['"us.census.tiger".baloney'], -- entry not in catalog
-    '2009 - 2013'
-  ))).*
-ORDER BY 1 ASC;
-
--- OBS_LookupCensusHuman
--- should give back: {"\"us.census.acs\".B19083001"}
-SELECT
-  cdb_observatory._OBS_LookupCensusHuman(
-    Array['gini_index']
-  );
-
--- should be empty array
-SELECT
-  cdb_observatory._OBS_LookupCensusHuman(
-    Array['cookies']
-  );
+  array_agg(a) expected from cdb_observatory._OBS_GetColumnData(
+    'us.census.tiger.census_tract',
+    Array['us.census.tiger.baloney'],
+    '2010 - 2014') a
+)
+select expected is null as OBS_GetColumnData_missing_measure
+from result;
 
 -- OBS_BuildSnapshotQuery
 -- Should give back: SELECT  vals[1] As total_pop, vals[2] As male_pop, vals[3] As female_pop, vals[4] As median_age
 SELECT
   cdb_observatory._OBS_BuildSnapshotQuery(
     Array['total_pop','male_pop','female_pop','median_age']
-  );
+  ) = 'SELECT  vals[1] As total_pop, vals[2] As male_pop, vals[3] As female_pop, vals[4] As median_age' As _OBS_BuildSnapshotQuery_test_1;
 
 -- should give back: SELECT  vals[1] As mandarin_orange
 SELECT
   cdb_observatory._OBS_BuildSnapshotQuery(
     Array['mandarin_orange']
-  );
+  ) = 'SELECT  vals[1] As mandarin_orange' As _OBS_BuildSnapshotQuery_test_2;
 
-\i test/sql/drop_fixtures.sql
+SELECT cdb_observatory._OBS_GetRelatedColumn(
+    Array[
+     'es.ine.pop_0_4',
+     'us.census.acs.B01003001',
+     'us.census.acs.B01001002'
+    ],
+     'denominator'
+ ) = '{es.ine.total_pop,NULL,us.census.acs.B01003001}' As _OBS_GetRelatedColumn_test;
+
+-- should give back a standardized measure name
+SELECT cdb_observatory._OBS_StandardizeMeasureName('test 343 %% 2 qqq }}{{}}') = 'test_343_2_qqq' As _OBS_StandardizeMeasureName_test;
+
+\i test/fixtures/drop_fixtures.sql

src/pg/test/sql/41_observatory_augmentation_test.sql

@@ -1,82 +1,76 @@
-\i test/sql/load_fixtures.sql
---
-SELECT * FROM
-  cdb_observatory._OBS_GetDemographicSnapshot(
-      cdb_observatory._TestPoint(),
-      '2009 - 2013',
-      '"us.census.tiger".block_group'
-  ) As snapshot;
+\i test/fixtures/load_fixtures.sql
+\pset format unaligned
+\set ECHO none
 
 --
--- dimension | dimension_value
--- ----------|----------------
--- total_pop | 9516.27915900609
--- male_pop  | 6152.51885204623
+WITH result as(
+  Select count(coalesce(OBS_GetDemographicSnapshot->>'value', 'foo')) expected_columns
+  FROM cdb_observatory.OBS_GetDemographicSnapshot(cdb_observatory._TestPoint())
+) select expected_columns = 52 as OBS_GetDemographicSnapshot_test_no_returns
+FROM result;
 
-SELECT *
-FROM
-  cdb_observatory._OBS_GetCensus(
-    cdb_observatory._TestPoint(),
-    Array['total_pop','male_pop']::text[]
-  );
-
--- what happens on null island?
--- expect nulls back: {female_pop, male_pop} | {NULL, NULL}
-SELECT *
-FROM
-  cdb_observatory._OBS_GetCensus(
-    ST_Buffer(CDB_LatLng(0, 0)::geography, 5000)::geometry,
-    Array['female_pop','male_pop']::text[]
-  );
--- expect nulls back {female_pop, male_pop} | {NULL, NULL}
-SELECT *
-FROM
-  cdb_observatory._OBS_GetCensus(
-    CDB_LatLng(0, 0),
-    Array['female_pop', 'male_pop']::text[]
-  );
-
---
--- names      | vals
--- -----------|-------
--- gini_index | 0.3494
-
-SELECT * FROM
+WITH result as (
+  SELECT _OBS_Get::text as expected FROM
   cdb_observatory._OBS_Get(
     cdb_observatory._TestPoint(),
-    Array['"us.census.acs".B19083001']::text[],
-    '2009 - 2013',
-    '"us.census.tiger".block_group'
-  );
+    Array['us.census.acs.B19013001']::text[],
+    '2010 - 2014',
+    'us.census.tiger.block_group'
+  )
+) SELECT expected = '{"value":79292,"name":"Median Household Income in the past 12 Months","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"median","type":"Numeric","description":"Within a geographic area, the median income received by every household on a regular basis before payments for personal income taxes, social security, union dues, medicare deductions, etc.  It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans'' (VA) payments, unemployment and/or worker''s compensation, child support, and alimony."}'
+  As OBS_Get_median_income_at_test_point
+  FROM result;
 
--- gini index at null island
-SELECT * FROM
+-- median income at null island
+WITH result as (
+  SELECT count(_OBS_Get) as expected FROM
   cdb_observatory._OBS_Get(
-    CDB_LatLng(0, 0),
-    Array['"us.census.acs".B19083001']::text[],
-    '2009 - 2013',
-    '"us.census.tiger".block_group'
-  );
+    ST_SetSRID(ST_Point(0, 0), 4326),
+    Array['us.census.acs.B19013001']::text[],
+    '2010 - 2014',
+    'us.census.tiger.block_group'
+  )
+) select expected = 0 as OBS_Get_median_income_at_null_island
+  from result;
 
 -- OBS_GetPoints
 -- obs_getpoints
 -- --------------------
 -- {4809.33511352425}
 
+-- SELECT
+--   (cdb_observatory._OBS_GetPoints(
+--     cdb_observatory._TestPoint(),
+--     'obs_c6fb99c47d61289fbb8e561ff7773799d3fcc308'::text, -- block groups (see _obs_geomtable)
+--     (Array['{"colname":"total_pop","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'::json])
+--   ))[1]::text = '{"value":10923.093200390833950,"name":"Total Population","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'
+--   as OBS_GetPoints_for_test_point;
+WITH cte As (
 SELECT
-  cdb_observatory._OBS_GetPoints(
+  (cdb_observatory._OBS_GetPoints(
     cdb_observatory._TestPoint(),
-    'obs_a92e1111ad3177676471d66bb8036e6d057f271b'::text, -- see example in obs_geomtable
-    Array[('total_pop','obs_ab038198aaab3f3cb055758638ee4de28ad70146','sum')::cdb_observatory.OBS_ColumnData]
-  );
+    'obs_c6fb99c47d61289fbb8e561ff7773799d3fcc308'::text, -- block groups (see _obs_geomtable)
+    (Array['{"colname":"total_pop","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'::json])
+  ))[1]
+  as OBS_GetPoints_for_test_point)
+SELECT
+  (abs((OBS_GetPoints_for_test_point ->> 'value')::numeric - 10923.093200390833950) / 10923.093200390833950) < 0.001 As OBS_GetPoints_for_test_point_value,
+  (OBS_GetPoints_for_test_point ->> 'name') = 'Total Population' As OBS_GetPoints_for_test_point_name,
+  (OBS_GetPoints_for_test_point ->> 'tablename') = 'obs_1a098da56badf5f32e336002b0a81708c40d29cd' As OBS_GetPoints_for_test_point_tablename,
+  (OBS_GetPoints_for_test_point ->> 'aggregate') = 'sum' As OBS_GetPoints_for_test_point_aggregate,
+  (OBS_GetPoints_for_test_point ->> 'type') = 'Numeric' As OBS_GetPoints_for_test_point_type,
+  (OBS_GetPoints_for_test_point ->> 'description') = 'The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates.' As OBS_GetPoints_for_test_point_description
+FROM cte;
 
 -- what happens at null island
+
 SELECT
-  cdb_observatory._OBS_GetPoints(
-    CDB_LatLng(0, 0),
-    'obs_a92e1111ad3177676471d66bb8036e6d057f271b'::text, -- see example in obs_geomtable
-    Array[('total_pop','obs_ab038198aaab3f3cb055758638ee4de28ad70146','sum')::cdb_observatory.OBS_ColumnData]
-  );
+  (cdb_observatory._OBS_GetPoints(
+    ST_SetSRID(ST_Point(0, 0), 4326),
+    'obs_1a098da56badf5f32e336002b0a81708c40d29cd'::text, -- see example in obs_geomtable
+    (Array['{"colname":"total_pop","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'::json])
+  ))[1]::text  is null
+  as OBS_GetPoints_for_null_island;
 
 -- OBS_GetPolygons
 --   obs_getpolygons
@@ -84,45 +78,130 @@ SELECT
 --  {12996.8172420752}
 
 SELECT
-  cdb_observatory._OBS_GetPolygons(
+  (cdb_observatory._OBS_GetPolygons(
     cdb_observatory._TestArea(),
-    'obs_a92e1111ad3177676471d66bb8036e6d057f271b'::text, -- see example in obs_geomtable
-    Array[('total_pop','obs_ab038198aaab3f3cb055758638ee4de28ad70146','sum')::cdb_observatory.OBS_ColumnData]
-);
+    'obs_c6fb99c47d61289fbb8e561ff7773799d3fcc308'::text, -- see example in obs_geomtable
+    Array['{"colname":"total_pop","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'::json]
+))[1]::text = '{"value":12327.3133495107,"name":"Total Population","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'
+  as OBS_GetPolygons_for_test_point;
 
 -- see what happens around null island
 SELECT
-  cdb_observatory._OBS_GetPolygons(
-    ST_Buffer(CDB_LatLng(0, 0)::geography, 500)::geometry,
-    'obs_a92e1111ad3177676471d66bb8036e6d057f271b'::text, -- see example in obs_geomtable
-    Array[('total_pop','obs_ab038198aaab3f3cb055758638ee4de28ad70146','sum')::cdb_observatory.OBS_ColumnData]
-);
+  ((cdb_observatory._OBS_GetPolygons(
+    ST_Buffer(ST_SetSRID(ST_Point(0, 0), 4326)::geography, 500)::geometry,
+    'obs_1a098da56badf5f32e336002b0a81708c40d29cd'::text, -- see example in obs_geomtable
+    Array['{"colname":"total_pop","tablename":"obs_1a098da56badf5f32e336002b0a81708c40d29cd","aggregate":"sum","name":"Total Population","type":"Numeric","description":"The total number of all people living in a given geographic area.  This is a very useful catch-all denominator when calculating rates."}'::json])
+  )[1]->>'value') is null
+  as OBS_GetPolygons_for_null_island;
 
-SELECT * FROM
-  cdb_observatory._OBS_GetSegmentSnapshot(
+SELECT cdb_observatory.OBS_GetSegmentSnapshot(
     cdb_observatory._TestPoint(),
-    '"us.census.tiger".census_tract'
-);
+    'us.census.tiger.census_tract'
+)::text =
+ '{"x10_segment":"Wealthy, urban without Kids","x55_segment":"Wealthy transplants displacing long-term local residents","us.census.acs.B01003001_quantile":"0.3235","us.census.acs.B01001002_quantile":"0.494716216216216","us.census.acs.B01001026_quantile":"0.183756756756757","us.census.acs.B01002001_quantile":"0.0752837837837838","us.census.acs.B03002003_quantile":"0.293162162162162","us.census.acs.B03002004_quantile":"0.455527027027027","us.census.acs.B03002006_quantile":"0.656405405405405","us.census.acs.B03002012_quantile":"0.840081081081081","us.census.acs.B05001006_quantile":"0.727135135135135","us.census.acs.B08006001_quantile":"0.688635135135135","us.census.acs.B08006002_quantile":"0.0204459459459459","us.census.acs.B08006008_quantile":"0.679324324324324","us.census.acs.B08006009_quantile":"0.996716216216216","us.census.acs.B08006011_quantile":"0.967418918918919","us.census.acs.B08006015_quantile":"0.512945945945946","us.census.acs.B08006017_quantile":"0.0504864864864865","us.census.acs.B09001001_quantile":"0.192405405405405","us.census.acs.B11001001_quantile":"0.331702702702703","us.census.acs.B14001001_quantile":"0.296283783783784","us.census.acs.B14001002_quantile":"0.045472972972973","us.census.acs.B14001005_quantile":"0.0442702702702703","us.census.acs.B14001006_quantile":"0.0829054054054054","us.census.acs.B14001007_quantile":"0.701135135135135","us.census.acs.B14001008_quantile":"0.404527027027027","us.census.acs.B15003001_quantile":"0.191824324324324","us.census.acs.B15003017_quantile":"0.864162162162162","us.census.acs.B15003022_quantile":"0.754297297297297","us.census.acs.B15003023_quantile":"0.350054054054054","us.census.acs.B16001001_quantile":"0.217635135135135","us.census.acs.B16001002_quantile":"0.85972972972973","us.census.acs.B16001003_quantile":"0.342851351351351","us.census.acs.B17001001_quantile":"0.51204054054054","us.census.acs.B17001002_quantile":"0.813540540540541","us.census.acs.B19013001_quantile":"0.0948648648648649","us.census.acs.B19083001_quantile":"0.678351351351351","us.census.acs.B19301001_quantile":"0.146108108108108","us.census.acs.B25001001_quantile":"0.149067567567568","us.census.acs.B25002003_quantile":"0","us.census.acs.B25004002_quantile":"0","us.census.acs.B25004004_quantile":"0.944554054054054","us.census.acs.B25058001_quantile":"0.398040540540541","us.census.acs.B25071001_quantile":"0.0596081081081081","us.census.acs.B25075001_quantile":"0","us.census.acs.B25075025_quantile":null}' as test_point_segmentation;
 
 -- segmentation around null island
-SELECT * FROM
-  cdb_observatory._OBS_GetSegmentSnapshot(
-    CDB_LatLng(0, 0),
-    '"us.census.tiger".census_tract'
-);
+SELECT cdb_observatory.OBS_GetSegmentSnapshot(
+    ST_SetSRID(ST_Point(0, 0), 4326),
+    'us.census.tiger.census_tract'
+)::text = '{"x10_segment":null,"x55_segment":null,"us.census.acs.B01003001_quantile":null,"us.census.acs.B01001002_quantile":null,"us.census.acs.B01001026_quantile":null,"us.census.acs.B01002001_quantile":null,"us.census.acs.B03002003_quantile":null,"us.census.acs.B03002004_quantile":null,"us.census.acs.B03002006_quantile":null,"us.census.acs.B03002012_quantile":null,"us.census.acs.B05001006_quantile":null,"us.census.acs.B08006001_quantile":null,"us.census.acs.B08006002_quantile":null,"us.census.acs.B08006008_quantile":null,"us.census.acs.B08006009_quantile":null,"us.census.acs.B08006011_quantile":null,"us.census.acs.B08006015_quantile":null,"us.census.acs.B08006017_quantile":null,"us.census.acs.B09001001_quantile":null,"us.census.acs.B11001001_quantile":null,"us.census.acs.B14001001_quantile":null,"us.census.acs.B14001002_quantile":null,"us.census.acs.B14001005_quantile":null,"us.census.acs.B14001006_quantile":null,"us.census.acs.B14001007_quantile":null,"us.census.acs.B14001008_quantile":null,"us.census.acs.B15003001_quantile":null,"us.census.acs.B15003017_quantile":null,"us.census.acs.B15003022_quantile":null,"us.census.acs.B15003023_quantile":null,"us.census.acs.B16001001_quantile":null,"us.census.acs.B16001002_quantile":null,"us.census.acs.B16001003_quantile":null,"us.census.acs.B17001001_quantile":null,"us.census.acs.B17001002_quantile":null,"us.census.acs.B19013001_quantile":null,"us.census.acs.B19083001_quantile":null,"us.census.acs.B19301001_quantile":null,"us.census.acs.B25001001_quantile":null,"us.census.acs.B25002003_quantile":null,"us.census.acs.B25004002_quantile":null,"us.census.acs.B25004004_quantile":null,"us.census.acs.B25058001_quantile":null,"us.census.acs.B25071001_quantile":null,"us.census.acs.B25075001_quantile":null,"us.census.acs.B25075025_quantile":null}' as null_island_segmentation;
 
-SELECT * FROM
-  cdb_observatory._OBS_GetCategories(
+WITH result as (
+  SELECT array_agg(_OBS_GetCategories) as expected FROM
+    cdb_observatory._OBS_GetCategories(
+      cdb_observatory._TestPoint(),
+      Array['us.census.spielman_singleton_segments.X10'],
+      'us.census.tiger.census_tract'
+  )
+)
+  select (expected)[1]::text = '{"category":"Wealthy, urban without Kids","name":"Spielman-Singleton Segments: 10 Clusters","tablename":"obs_65f29658e096ca1485bf683f65fdbc9f05ec3c5d","aggregate":null,"type":"Text","description":"Sociodemographic classes from Spielman and Singleton 2015, 10 clusters"}' as GetCategories_at_test_point_1
+  from result;
+
+WITH result as (
+  SELECT array_agg(_OBS_GetCategories) as expected FROM
+    cdb_observatory._OBS_GetCategories(
+      ST_SetSRID(ST_Point(0,0), 4326),
+      Array['us.census.spielman_singleton_segments.X10'],
+      'us.census.tiger.census_tract'
+  )
+)
+  select expected[0] is NULL as GetCategories_at_null_island
+  from result;
+
+-- Point-based OBS_GetMeasure with zillow
+SELECT abs(OBS_GetMeasure_zhvi_point - 583600) / 583600 < 0.001 AS OBS_GetMeasure_zhvi_point_test FROM cdb_observatory.OBS_GetMeasure(
+  ST_SetSRID(ST_Point(-73.94602417945862, 40.6768220087458), 4326),
+  'us.zillow.AllHomes_Zhvi', 'area', 'us.census.tiger.zcta5', '2014-01'
+) As t(OBS_GetMeasure_zhvi_point);
+
+-- Point-based OBS_GetMeasure with zillow default to latest
+SELECT abs(OBS_GetMeasure_zhvi_point_default_latest - 972900) / 972900 < 0.001 AS OBS_GetMeasure_zhvi_point_default_latest_test FROM cdb_observatory.OBS_GetMeasure(
+  ST_SetSRID(ST_Point(-73.94602417945862, 40.6768220087458), 4326),
+  'us.zillow.AllHomes_Zhvi'
+) As t(OBS_GetMeasure_zhvi_point_default_latest);
+
+-- Point-based OBS_GetMeasure, default normalization (area)
+-- is result within 0.1% of expected
+SELECT abs(OBS_GetMeasure_total_pop_point - 10923.093200390833950) / 10923.093200390833950 < 0.001 As OBS_GetMeasure_total_pop_point_test FROM
+  cdb_observatory.OBS_GetMeasure(
     cdb_observatory._TestPoint(),
-    Array['"us.census.spielman_singleton_segments".X10'],
-    '"us.census.tiger".census_tract'
-);
+    'us.census.acs.B01003001'
+) As t(OBS_GetMeasure_total_pop_point);
 
-SELECT * FROM
-  cdb_observatory._OBS_GetCategories(
-    CDB_LatLng(0, 0),
-    Array['"us.census.spielman_singleton_segments".X10'],
-    '"us.census.tiger".census_tract'
-);
+-- Poly-based OBS_GetMeasure, default normalization (none)
+-- is result within 0.1% of expected
+SELECT abs(OBS_GetMeasure_total_pop_polygon - 9833.47316573952) / 9833.47316573952 < 0.001 As OBS_GetMeasure_total_pop_polygon_test FROM
+  cdb_observatory.OBS_GetMeasure(
+    cdb_observatory._TestArea(),
+    'us.census.acs.B01003001'
+) As t(OBS_GetMeasure_total_pop_polygon);
 
-\i test/sql/drop_fixtures.sql
+-- Point-based OBS_GetMeasure with denominator normalization
+SELECT (abs(cdb_observatory.OBS_GetMeasure(
+  cdb_observatory._TestPoint(),
+  'us.census.acs.B01001002', 'denominator') - 0.62157894736842105263) / 0.62157894736842105263) < 0.001 As OBS_GetMeasure_total_male_point_denominator;
+
+-- Poly-based OBS_GetMeasure with denominator normalization
+SELECT abs(cdb_observatory.OBS_GetMeasure(
+  cdb_observatory._TestArea(),
+  'us.census.acs.B01001002', 'denominator') - 0.50597531462834994530) / 0.49026340444793965457 < 0.001 As OBS_GetMeasure_total_male_poly_denominator;
+
+-- Point-based OBS_GetCategory
+SELECT cdb_observatory.OBS_GetCategory(
+  cdb_observatory._TestPoint(), 'us.census.spielman_singleton_segments.X10') = 'Wealthy, urban without Kids' As OBS_GetCategory_point;
+
+-- Poly-based OBS_GetCategory
+SELECT cdb_observatory.OBS_GetCategory(
+  cdb_observatory._TestArea(), 'us.census.spielman_singleton_segments.X10') = 'Low income, mix of minorities' As obs_getcategory_polygon;
+
+-- Point-based OBS_GetPopulation, default normalization (area)
+SELECT (abs(OBS_GetPopulation - 10923.093200390833950) / 10923.093200390833950) < 0.001 As OBS_GetPopulation FROM
+  cdb_observatory.OBS_GetPopulation(
+    cdb_observatory._TestPoint()
+  ) As m(OBS_GetPopulation);
+
+-- Poly-based OBS_GetPopulation, default normalization (none)
+SELECT (abs(obs_getpopulation_polygon - 9833.47316573952) / 9833.47316573952) < 0.001 As obs_getpopulation_polygon_test
+FROM
+  cdb_observatory.OBS_GetPopulation(
+    cdb_observatory._TestArea()
+  ) As m(obs_getpopulation_polygon);
+
+-- Point-based OBS_GetUSCensusMeasure, default normalization (area)
+SELECT (abs(cdb_observatory.obs_getuscensusmeasure(
+  cdb_observatory._testpoint(), 'male population') - 6789.5647735060920500) / 6789.5647735060920500) < 0.001 As obs_getuscensusmeasure_point_male_pop;
+
+-- Poly-based OBS_GetUSCensusMeasure, default normalization (none)
+SELECT (abs(cdb_observatory.obs_getuscensusmeasure(
+  cdb_observatory._testarea(), 'male population') - 4975.49467892449) / 4975.49467892449) < 0.001 As obs_getuscensusmeasure;
+
+-- Point-based OBS_GetUSCensusCategory
+SELECT cdb_observatory.OBS_GetUSCensusCategory(
+  cdb_observatory._testpoint(), 'Spielman-Singleton Segments: 10 Clusters') = 'Wealthy, urban without Kids' As OBS_GetUSCensusCategory_point;
+
+-- Area-based OBS_GetUSCensusCategory
+SELECT cdb_observatory.OBS_GetUSCensusCategory(
+  cdb_observatory._testarea(), 'Spielman-Singleton Segments: 10 Clusters') = 'Low income, mix of minorities' As OBS_GetUSCensusCategory_polygon;
+
+
+\i test/fixtures/drop_fixtures.sql

src/pg/test/sql/42_observatory_exploration_test.sql

@@ -0,0 +1,33 @@
+\i test/fixtures/load_fixtures.sql
+\pset format unaligned
+
+-- set up variables for use in testing
+
+\set cartodb_census_tract_geometry ''
+
+\set cartodb_county_geometry ''
+
+-- _OBS_SearchTables tests
+SELECT
+  t.table_name = 'obs_1babf5a26a1ecda5fb74963e88408f71d0364b81' As _OBS_SearchTables_tables_match,
+  t.timespan = '2014' As _OBS_SearchTables_timespan_matches
+FROM cdb_observatory._OBS_SearchTables(
+  'us.census.tiger.county',
+  '2014'
+) As t(table_name, timespan);
+
+-- _OBS_SearchTables tests
+-- should not return tables for year that does not match
+SELECT count(*) = 0 As _OBS_SearchTables_timespan_does_not_match
+FROM cdb_observatory._OBS_SearchTables(
+  'us.census.tiger.county',
+  '1988' -- year before first tiger data was collected
+) As t(table_name, timespan);
+
+SELECT *
+FROM cdb_observatory.OBS_Search('total_pop');
+
+SELECT *
+FROM cdb_observatory.OBS_GetAvailableBoundaries(cdb_observatory._TestPoint());
+
+\i test/fixtures/drop_fixtures.sql

src/pg/test/sql/drop_fixtures.sql

@@ -1,46 +0,0 @@
-SET client_min_messages TO NOTICE;
-\set ECHO none
-
--- metadata
-\echo Dropping obs_table.sql fixture table...
-DROP TABLE observatory.obs_table;
-\echo Done.
-
-\echo Dropping obs_column.sql fixture table...
-DROP TABLE observatory.obs_column;
-\echo Done.
-
-\echo Dropping obs_column_table.sql fixture table...
-DROP TABLE observatory.obs_column_table;
-\echo Done.
-
-\echo Dropping obs_column_to_column.sql fixture table...
-DROP TABLE observatory.obs_column_to_column;
-\echo Done.
-
--- data
-\echo Dropping obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1 fixture table...
-DROP TABLE observatory.obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1;
-\echo Done.
-
-\echo Dropping obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb fixture table...
-DROP TABLE observatory.obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb;
-\echo Done.
-
-\echo Dropping obs_ab038198aaab3f3cb055758638ee4de28ad70146 fixture table...
-DROP TABLE observatory.obs_ab038198aaab3f3cb055758638ee4de28ad70146;
-\echo Done.
-
-\echo Dropping obs_a92e1111ad3177676471d66bb8036e6d057f271b fixture table...
-DROP TABLE observatory.obs_a92e1111ad3177676471d66bb8036e6d057f271b;
-\echo Done.
-
-\echo Dropping obs_11ee8b82c877c073438bc935a91d3dfccef875d1 fixture table...
-DROP TABLE observatory.obs_11ee8b82c877c073438bc935a91d3dfccef875d1;
-\echo Done.
-
-\echo Dropping obs_d34555209878e8c4b37cf0b2b3d072ff129ec470 fixture table...
-DROP TABLE observatory.obs_d34555209878e8c4b37cf0b2b3d072ff129ec470;
-\echo Done.
-
-\unset ECHO

src/pg/test/sql/load_fixtures.sql

@@ -1,46 +0,0 @@
-SET client_min_messages TO WARNING;
-\set ECHO none
-
--- metadata
-\echo Loading obs_table.sql fixture file...
-\i test/fixtures/obs_table.sql
-\echo Done.
-
-\echo Loading obs_column.sql fixture file...
-\i test/fixtures/obs_column.sql
-\echo Done.
-
-\echo Loading obs_column_table.sql fixture file...
-\i test/fixtures/obs_column_table.sql
-\echo Done.
-
-\echo Loading obs_column_to_column.sql fixture file...
-\i test/fixtures/obs_column_to_column.sql
-\echo Done.
-
--- data
-\echo Loading obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1.sql fixture file...
-\i test/fixtures/obs_85328201013baa14e8e8a4a57a01e6f6fbc5f9b1.sql
-\echo Done.
-
-\echo Loading obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb.sql fixture file...
-\i test/fixtures/obs_3e7cc9cfd403b912c57b42d5f9195af9ce2f3cdb.sql
-\echo Done.
-
-\echo Loading obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql fixture file...
-\i test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql
-\echo Done.
-
-\echo Loading obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql fixture file...
-\i test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql
-\echo Done.
-
-\echo Loading obs_11ee8b82c877c073438bc935a91d3dfccef875d1.sql fixture file...
-\i test/fixtures/obs_11ee8b82c877c073438bc935a91d3dfccef875d1.sql
-\echo Done.
-
-\echo Loading obs_d34555209878e8c4b37cf0b2b3d072ff129ec470.sql fixture file...
-\i test/fixtures/obs_d34555209878e8c4b37cf0b2b3d072ff129ec470.sql
-\echo Done.
-
-\unset ECHO