Merge pull request #193 from CartoDB/add-schema-to-docs-examples

updates examples to include schema
2018-01-09 10:51:49 -05:00
parent 0194c036f6 92becac280
commit f1428a3e36
11 changed files with 128 additions and 63 deletions
--- a/doc/02_moran.md
+++ b/doc/02_moran.md
@@ -37,8 +37,10 @@ SELECT
  aoi.quads,
  aoi.significance,
  c.num_cyclists_per_total_population
-FROM CDB_AreasOfInterestLocal('SELECT * FROM commute_data'
-                                 'num_cyclists_per_total_population') As aoi
+FROM
+  cdb_crankshaft.CDB_AreasOfInterestLocal(
+    'SELECT * FROM commute_data'
+    'num_cyclists_per_total_population') As aoi
 JOIN commute_data As c
 ON c.cartodb_id = aoi.rowid;
 ```
@@ -71,8 +73,12 @@ A table with the following columns.
 #### Examples

 ```sql
-SELECT *
-FROM CDB_AreasOfInterestGlobal('SELECT * FROM commute_data', 'num_cyclists_per_total_population')
+SELECT
+    *
+FROM
+    cdb_crankshaft.CDB_AreasOfInterestGlobal(
+        'SELECT * FROM commute_data',
+        'num_cyclists_per_total_population')
 ```

 ### CDB_AreasOfInterestLocalRate(subquery text, numerator_column text, denominator_column text)
@@ -113,9 +119,11 @@ SELECT
  aoi.quads,
  aoi.significance,
  c.cyclists_per_total_population
-FROM CDB_AreasOfInterestLocalRate('SELECT * FROM commute_data'
-                                     'num_cyclists',
-                                     'total_population') As aoi
+FROM
+    cdb_crankshaft.CDB_AreasOfInterestLocalRate(
+        'SELECT * FROM commute_data'
+        'num_cyclists',
+        'total_population') As aoi
 JOIN commute_data As c
 ON c.cartodb_id = aoi.rowid;
 ```
@@ -149,10 +157,13 @@ A table with the following columns.
 #### Examples

 ```sql
-SELECT *
-FROM CDB_AreasOfInterestGlobalRate('SELECT * FROM commute_data',          
-                                   'num_cyclists',
-                                   'total_population')
+SELECT
+    *
+FROM
+    cdb_crankshaft.CDB_AreasOfInterestGlobalRate(
+        'SELECT * FROM commute_data',
+        'num_cyclists',
+        'total_population')
 ```

 ## Hotspot, Coldspot, and Outlier Functions
--- a/doc/04_markov.md
+++ b/doc/04_markov.md
@@ -40,8 +40,12 @@ SELECT
  m.trend_up,
  m.trend_down,
  m.volatility
-FROM CDB_SpatialMarkovTrend('SELECT * FROM nyc_real_estate'
-                            Array['m03y2009','m03y2010','m03y2011','m03y2012','m03y2013','m03y2014','m03y2015','m03y2016']) As m
+FROM
+  cdb_crankshaft.CDB_SpatialMarkovTrend(
+    'SELECT * FROM nyc_real_estate'
+    Array['m03y2009', 'm03y2010', 'm03y2011',
+          'm03y2012', 'm03y2013', 'm03y2014',
+          'm03y2015','m03y2016']) As m
 JOIN nyc_real_estate As c
 ON c.cartodb_id = m.rowid;
 ```
--- a/doc/07_gravity.md
+++ b/doc/07_gravity.md
@@ -54,9 +54,9 @@ with t as (
 SELECT
    array_agg(cartodb_id::bigint) as id,
    array_agg(the_geom) as g,
-    array_agg(coalesce(gla,0)::numeric) as w
+    array_agg(coalesce(gla, 0)::numeric) as w
 FROM
-    abel.centros_comerciales_de_madrid
+    centros_comerciales_de_madrid
 WHERE not no_cc
 ),
 s as (
@@ -67,12 +67,15 @@ SELECT
 FROM
    sscc_madrid
 )
-select
+SELECT
    g.the_geom,
-    trunc(g.h,2) as h,
+    trunc(g.h, 2) as h,
    round(g.hpop) as hpop,
-    trunc(g.dist/1000,2) as dist_km
-FROM t, s, CDB_Gravity1(t.id, t.g, t.w, s.id, s.g, s.p, newmall_ID, 100000, 5000) g
+    trunc(g.dist/1000, 2) as dist_km
+FROM
+    t,
+    s,
+    cdb_crankshaft.CDB_Gravity(t.id, t.g, t.w, s.id, s.g, s.p, newmall_ID, 100000, 5000) as g
 ```


--- a/doc/08_interpolation.md
+++ b/doc/08_interpolation.md
@@ -44,11 +44,18 @@ Default values:
 #### Example Usage

 ```sql
-with a as (
-    select
+WITH a as (
+    SELECT
        array_agg(the_geom) as geomin,
        array_agg(temp::numeric) as colin
-    from table_4804232032
+    FROM table_4804232032
 )
-SELECT CDB_SpatialInterpolation(geomin, colin, CDB_latlng(41.38, 2.15),1) FROM a;
+SELECT
+    cdb_crankshaft.CDB_SpatialInterpolation(
+        geomin,
+        colin,
+        CDB_latlng(41.38, 2.15),
+        1)
+FROM
+    a
 ```
--- a/doc/09_voronoi.md
+++ b/doc/09_voronoi.md
@@ -27,12 +27,20 @@ PostGIS wil include this in future versions ([doc for dev branch](http://postgis
 ```sql
 WITH a AS (
    SELECT
-    ARRAY[ST_GeomFromText('POINT(2.1744 41.403)', 4326),ST_GeomFromText('POINT(2.1228 41.380)', 4326),ST_GeomFromText('POINT(2.1511 41.374)', 4326),ST_GeomFromText('POINT(2.1528 41.413)', 4326),ST_GeomFromText('POINT(2.165 41.391)', 4326),ST_GeomFromText('POINT(2.1498 41.371)', 4326),ST_GeomFromText('POINT(2.1533 41.368)', 4326),ST_GeomFromText('POINT(2.131386 41.41399)', 4326)] AS geomin
+        ARRAY[
+            ST_GeomFromText('POINT(2.1744 41.403)', 4326),
+            ST_GeomFromText('POINT(2.1228 41.380)', 4326),
+            ST_GeomFromText('POINT(2.1511 41.374)', 4326),
+            ST_GeomFromText('POINT(2.1528 41.413)', 4326),
+            ST_GeomFromText('POINT(2.165 41.391)', 4326),
+            ST_GeomFromText('POINT(2.1498 41.371)', 4326),
+            ST_GeomFromText('POINT(2.1533 41.368)', 4326),
+            ST_GeomFromText('POINT(2.131386 41.41399)', 4326)
+        ] AS geomin
 )
 SELECT
-    st_transform(
-    (st_dump(CDB_voronoi(geomin, 0.2, 1e-9)
-    )).geom
-        , 3857) as the_geom_webmercator
+    ST_TRANSFORM(
+        (ST_Dump(cdb_crankshaft.CDB_Voronoi(geomin, 0.2, 1e-9))).geom,
+        3857) as the_geom_webmercator
 FROM a;
 ```
--- a/doc/11_kmeans.md
+++ b/doc/11_kmeans.md
@@ -1,8 +1,8 @@
 ## K-Means Functions

-### CDB_KMeans(subquery text, no_clusters INTEGER)
+### CDB_KMeans(subquery text, no_clusters integer)

-This function attempts to find n clusters within the input data. It will return a table to CartoDB ids and 
+This function attempts to find n clusters within the input data. It will return a table to CartoDB ids and
 the number of the cluster each point in the input was assigend to.


@@ -26,18 +26,20 @@ A table with the following columns.
 #### Example Usage

 ```sql
-SELECT 
-    customers.*, 
-    km.cluster_no 
-    FROM cdb_crankshaft.CDB_Kmeans('SELECT * from customers' , 6) km, customers_3
-    WHERE customers.cartodb_id = km.cartodb_id
+SELECT
+    customers.*,
+    km.cluster_no
+FROM
+   cdb_crankshaft.CDB_Kmeans('SELECT * from customers' , 6) km, customers_3
+WHERE
+    customers.cartodb_id = km.cartodb_id
 ```

 ### CDB_WeightedMean(subquery text, weight_column text, category_column text)

 Function that computes the weighted centroid of a number of clusters by some weight column.

-### Arguments 
+### Arguments

 | Name | Type | Description |
 |------|------|-------------|
@@ -45,18 +47,24 @@ Function that computes the weighted centroid of a number of clusters by some wei
 | weight\_column | TEXT | The name of the column to use as a weight |
 | category\_column | TEXT | The name of the column to use as a category |

-### Returns 
+### Returns

 A table with the following columns.

 | Column Name | Type | Description |
 |-------------|------|-------------|
 | the\_geom | GEOMETRY | A point for the weighted cluster center |
-| class | INTEGER | The cluster class | 
+| class | INTEGER | The cluster class |

-### Example Usage 
+### Example Usage

-```sql 
-SELECT ST_TRANSFORM(the_geom, 3857) as the_geom_webmercator, class 
-FROM cdb_weighted_mean('SELECT *, customer_value FROM customers','customer_value','cluster_no')
+```sql
+SELECT
+    ST_Transform(m.the_geom, 3857) AS the_geom_webmercator,
+    m.class
+FROM
+    cdb_crankshaft.cdb_WeightedMean(
+        'SELECT * FROM customers',
+        'customer_value',
+        'cluster_no') AS m
 ```
--- a/doc/12_segmentation.md
+++ b/doc/12_segmentation.md
@@ -3,7 +3,7 @@

 ### CDB_CreateAndPredictSegment(query TEXT, variable_name TEXT, target_query TEXT)

-This function trains a [Gradient Boosting](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) model to attempt to predict the target data and then generates predictions for new data.  
+This function trains a [Gradient Boosting](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) model to attempt to predict the target data and then generates predictions for new data.

 #### Arguments

@@ -34,12 +34,12 @@ A table with the following columns.
 SELECT * from cdb_crankshaft.CDB_CreateAndPredictSegment(
 'SELECT agg, median_rent::numeric, male_pop::numeric, female_pop::numeric FROM late_night_agg',
 'agg',
-'SELECT row_number() OVER () As cartodb_id, median_rent, male_pop, female_pop FROM ml_learning_ny');                               
+'SELECT row_number() OVER () As cartodb_id, median_rent, male_pop, female_pop FROM ml_learning_ny');
 ```

 ### CDB_CreateAndPredictSegment(target numeric[], train_features numeric[], prediction_features numeric[], prediction_ids numeric[])

-This function trains a [Gradient Boosting](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) model to attempt to predict the target data and then generates predictions for new data.  
+This function trains a [Gradient Boosting](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) model to attempt to predict the target data and then generates predictions for new data.


 #### Arguments
@@ -76,7 +76,7 @@ WITH training As (
    FROM late_night_agg),
 target AS (
    SELECT cdb_crankshaft.CDB_PyAgg(Array[median_rent, male_pop, female_pop]::Numeric[]) As features,
-     array_agg(cartodb_id) As cartodb_ids FROM late_night_agg)  
+     array_agg(cartodb_id) As cartodb_ids FROM late_night_agg)

 SELECT cdb_crankshaft.CDB_CreateAndPredictSegment(training.target, training.features, target.features, target.cartodb_ids)
 FROM training, target;
--- a/doc/13_PIA.md
+++ b/doc/13_PIA.md
@@ -23,11 +23,17 @@ Function to find the [PIA](https://en.wikipedia.org/wiki/Pole_of_inaccessibility
 #### Example Usage

 ```sql
-with a as(
- select st_geomfromtext('POLYGON((-432540.453078056 4949775.20452642,-432329.947920966 4951361.232584,-431245.028163694 4952223.31516671,-429131.071033529 4951768.00415574,-424622.07505895 4952843.13503987,-423688.327170174 4953499.20752423,-424086.294349759 4954968.38274191,-423068.388925945 4954378.63345336,-423387.653225542 4953355.67417084,-420594.869840519 4953781.00230592,-416026.095299382 4951484.06849063,-412483.018546414 4951024.5410983,-410490.399661215 4954502.24032205,-408186.197521284 4956398.91417441,-407627.262358013 4959300.94633864,-406948.770061627 4959874.85407739,-404949.583326472 4959047.74518163,-402570.908447199 4953743.46829807,-400971.358683991 4952193.11680804,-403533.488084088 4949649.89857885,-406335.177028373 4950193.19571096,-407790.456731515 4952391.46015616,-412060.672398345 4950381.2389307,-410716.93482498 4949156.7509561,-408464.162289794 4943912.8940387,-409350.599394983 4942819.84896006,-408087.791091424 4942451.6711778,-407274.045613725 4940572.4807777,-404446.196589102 4939976.71501489,-402422.964843936 4940450.3670813,-401010.654464241 4939054.8061663,-397647.247369412 4940679.80737878,-395658.413346901 4940528.84765185,-395536.852462953 4938829.79565997,-394268.923462818 4938003.7277717,-393388.720249116 4934757.80596815,-392393.301362444 4934326.71675815,-392573.527618037 4932323.40974412,-393464.640141837 4931903.10653605,-393085.597275686 4931094.7353605,-398426.261165985 4929156.87541607,-398261.174361137 4926238.00816416,-394045.059966834 4925765.18668498,-392982.960705174 4926391.81893628,-393090.272694301 4927176.84692181,-391648.240010564 4924626.06386961,-391889.914625075 4923086.14787613,-394345.177314013 4923235.086036,-395550.878718795 4917812.79243978,-399009.463978251 4912927.7157945,-398948.794855767 4911941.91010796,-398092.636652078 4911806.57392519,-401991.601817112 4911722.9204501,-406225.972607907 4914505.47286319,-411104.994569885 4912569.26941163,-412925.513522316 4913030.3608866,-414630.148884835 4914436.69169949,-414207.691417276 4919205.78028405,-418306.141109809 4917994.9580478,-424184.700779621 4918938.12432889,-426816.961458921 4923664.37379373,-420956.324227126 4923381.98014807,-420186.661267781 4924286.48693378,-420943.411166194 4926812.76394433,-419779.45457046 4928527.43466337,-419768.767899344 4930681.94459216,-421911.668097113 4930432.40620397,-423482.386112205 4933451.28047252,-427272.814773717 4934151.56473242,-427144.908678797 4939731.77191996,-428982.125554848 4940522.84445172,-428986.133056516 4942437.17281266,-431237.792396792 4947309.68284815,-432476.889648814 4947791.74800037,-432540.453078056 4949775.20452642))', 3857) as g
+WITH a as (
+    SELECT
+        ST_GeomFromText(
+            'POLYGON((-432540.453078056 4949775.20452642,-432329.947920966 4951361.232584,-431245.028163694 4952223.31516671,-429131.071033529 4951768.00415574,-424622.07505895 4952843.13503987,-423688.327170174 4953499.20752423,-424086.294349759 4954968.38274191,-423068.388925945 4954378.63345336,-423387.653225542 4953355.67417084,-420594.869840519 4953781.00230592,-416026.095299382 4951484.06849063,-412483.018546414 4951024.5410983,-410490.399661215 4954502.24032205,-408186.197521284 4956398.91417441,-407627.262358013 4959300.94633864,-406948.770061627 4959874.85407739,-404949.583326472 4959047.74518163,-402570.908447199 4953743.46829807,-400971.358683991 4952193.11680804,-403533.488084088 4949649.89857885,-406335.177028373 4950193.19571096,-407790.456731515 4952391.46015616,-412060.672398345 4950381.2389307,-410716.93482498 4949156.7509561,-408464.162289794 4943912.8940387,-409350.599394983 4942819.84896006,-408087.791091424 4942451.6711778,-407274.045613725 4940572.4807777,-404446.196589102 4939976.71501489,-402422.964843936 4940450.3670813,-401010.654464241 4939054.8061663,-397647.247369412 4940679.80737878,-395658.413346901 4940528.84765185,-395536.852462953 4938829.79565997,-394268.923462818 4938003.7277717,-393388.720249116 4934757.80596815,-392393.301362444 4934326.71675815,-392573.527618037 4932323.40974412,-393464.640141837 4931903.10653605,-393085.597275686 4931094.7353605,-398426.261165985 4929156.87541607,-398261.174361137 4926238.00816416,-394045.059966834 4925765.18668498,-392982.960705174 4926391.81893628,-393090.272694301 4927176.84692181,-391648.240010564 4924626.06386961,-391889.914625075 4923086.14787613,-394345.177314013 4923235.086036,-395550.878718795 4917812.79243978,-399009.463978251 4912927.7157945,-398948.794855767 4911941.91010796,-398092.636652078 4911806.57392519,-401991.601817112 4911722.9204501,-406225.972607907 4914505.47286319,-411104.994569885 4912569.26941163,-412925.513522316 4913030.3608866,-414630.148884835 4914436.69169949,-414207.691417276 4919205.78028405,-418306.141109809 4917994.9580478,-424184.700779621 4918938.12432889,-426816.961458921 4923664.37379373,-420956.324227126 4923381.98014807,-420186.661267781 4924286.48693378,-420943.411166194 4926812.76394433,-419779.45457046 4928527.43466337,-419768.767899344 4930681.94459216,-421911.668097113 4930432.40620397,-423482.386112205 4933451.28047252,-427272.814773717 4934151.56473242,-427144.908678797 4939731.77191996,-428982.125554848 4940522.84445172,-428986.133056516 4942437.17281266,-431237.792396792 4947309.68284815,-432476.889648814 4947791.74800037,-432540.453078056 4949775.20452642))',
+            3857) as g
 ),
 b as (
-    select ST_Transform(g, 4326) as g from a
+    SELECT ST_Transform(g, 4326) as g
+    FROM a
 )
-SELECT st_astext(CDB_PIA(g)) from b;
+SELECT
+    ST_AsText(cdb_crankshaft.CDB_PIA(g))
+FROM b
 ```
--- a/doc/14_densify.md
+++ b/doc/14_densify.md
@@ -24,12 +24,22 @@ Returns a table object
 #### Example Usage

 ```sql
-with data as (
-    select
-    ARRAY[7.0,8.0,1.0,2.0,3.0,5.0,6.0,4.0] as colin,
-    ARRAY[ST_GeomFromText('POINT(2.1744 41.4036)'),ST_GeomFromText('POINT(2.1228 41.3809)'),ST_GeomFromText('POINT(2.1511 41.3742)'),ST_GeomFromText('POINT(2.1528 41.4136)'),ST_GeomFromText('POINT(2.165 41.3917)'),ST_GeomFromText('POINT(2.1498 41.3713)'),ST_GeomFromText('POINT(2.1533 41.3683)'),ST_GeomFromText('POINT(2.131386 41.413998)')] as geomin
+WITH data as (
+    SELECT
+        ARRAY[7.0,8.0,1.0,2.0,3.0,5.0,6.0,4.0] as colin,
+        ARRAY[
+            ST_GeomFromText('POINT(2.1744 41.4036)'),
+            ST_GeomFromText('POINT(2.1228 41.3809)'),
+            ST_GeomFromText('POINT(2.1511 41.3742)'),
+            ST_GeomFromText('POINT(2.1528 41.4136)'),
+            ST_GeomFromText('POINT(2.165 41.3917)'),
+            ST_GeomFromText('POINT(2.1498 41.3713)'),
+            ST_GeomFromText('POINT(2.1533 41.3683)'),
+            ST_GeomFromText('POINT(2.131386 41.413998)')
+        ] as geomin
 )
-select CDB_Densify(geomin, colin, 2) from data;
+SELECT cdb_crankshaft.CDB_Densify(geomin, colin, 2)
+FROM data
 ```


--- a/doc/15_tinmap.md
+++ b/doc/15_tinmap.md
@@ -26,11 +26,19 @@ Returns a table object
 #### Example Usage

 ```sql
-with data as (
-    select
-    ARRAY[7.0,8.0,1.0,2.0,3.0,5.0,6.0,4.0] as colin,
-    ARRAY[ST_GeomFromText('POINT(2.1744 41.4036)'),ST_GeomFromText('POINT(2.1228 41.3809)'),ST_GeomFromText('POINT(2.1511 41.3742)'),ST_GeomFromText('POINT(2.1528 41.4136)'),ST_GeomFromText('POINT(2.165 41.3917)'),ST_GeomFromText('POINT(2.1498 41.3713)'),ST_GeomFromText('POINT(2.1533 41.3683)'),ST_GeomFromText('POINT(2.131386 41.413998)')] as geomin
+WITH data as (
+    SELECT
+        ARRAY[7.0,8.0,1.0,2.0,3.0,5.0,6.0,4.0] as colin,
+        ARRAY[ST_GeomFromText('POINT(2.1744 41.4036)'),
+			ST_GeomFromText('POINT(2.1228 41.3809)'),
+			ST_GeomFromText('POINT(2.1511 41.3742)'),
+			ST_GeomFromText('POINT(2.1528 41.4136)'),
+			ST_GeomFromText('POINT(2.165 41.3917)'),
+			ST_GeomFromText('POINT(2.1498 41.3713)'),
+			ST_GeomFromText('POINT(2.1533 41.3683)'),
+			ST_GeomFromText('POINT(2.131386 41.413998)')] as geomin
 )
-select CDB_TINmap(geomin, colin, 2) from data;
+SELECT cdb_crankshaft.CDB_TINmap(geomin, colin, 2)
+FROM data
 ```

--- a/doc/18_outliers.md
+++ b/doc/18_outliers.md
@@ -43,7 +43,7 @@ With a table `website_visits` and a column of the number of website visits in un
 ```sql
 SELECT
  id,
-  CDB_StaticOutlier(visits_10k, 11.0) As outlier,
+  cdb_crankshaft.CDB_StaticOutlier(visits_10k, 11.0) As outlier,
  visits_10k
 FROM website_visits
 ```
@@ -93,7 +93,7 @@ WITH cte As (
    unnest(Array[1,3,5,1,32,3,57,2]) As visits_10k
  )
 SELECT
-  (CDB_PercentOutlier(array_agg(visits_10k), 2.0, array_agg(id))).*
+  (cdb_crankshaft.CDB_PercentOutlier(array_agg(visits_10k), 2.0, array_agg(id))).*
 FROM cte;
 ```

@@ -144,7 +144,7 @@ WITH cte As (
    unnest(Array[1,3,5,1,32,3,57,2]) As visits_10k
  )
 SELECT
-  (CDB_StdDevOutlier(array_agg(visits_10k), 2.0, array_agg(id))).*
+  (cdb_crankshaft.CDB_StdDevOutlier(array_agg(visits_10k), 2.0, array_agg(id))).*
 FROM cte;
 ```