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syntax fixes / function name fix

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This commit is contained in:
Andy Eschbacher 2018-01-08 16:30:03 -05:00
parent e28f00d98b
commit 92becac280
4 changed files with 54 additions and 31 deletions
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33
doc/02_moran.md
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@ -37,8 +37,10 @@ SELECT
aoi.quads, aoi.quads,
aoi.significance, aoi.significance,
c.num_cyclists_per_total_population c.num_cyclists_per_total_population
FROM cdb_crankshaft.CDB_AreasOfInterestLocal('SELECT * FROM commute_data' FROM
'num_cyclists_per_total_population') As aoi cdb_crankshaft.CDB_AreasOfInterestLocal(
'SELECT * FROM commute_data'
'num_cyclists_per_total_population') As aoi
JOIN commute_data As c JOIN commute_data As c
ON c.cartodb_id = aoi.rowid; ON c.cartodb_id = aoi.rowid;
``` ```
@ -71,8 +73,12 @@ A table with the following columns.
#### Examples #### Examples
```sql ```sql
SELECT * SELECT
FROM cdb_crankshaft.CDB_AreasOfInterestGlobal('SELECT * FROM commute_data', 'num_cyclists_per_total_population') *
FROM
cdb_crankshaft.CDB_AreasOfInterestGlobal(
'SELECT * FROM commute_data',
'num_cyclists_per_total_population')
``` ```
### CDB_AreasOfInterestLocalRate(subquery text, numerator_column text, denominator_column text) ### CDB_AreasOfInterestLocalRate(subquery text, numerator_column text, denominator_column text)
@ -113,9 +119,11 @@ SELECT
aoi.quads, aoi.quads,
aoi.significance, aoi.significance,
c.cyclists_per_total_population c.cyclists_per_total_population
FROM cdb_crankshaft.CDB_AreasOfInterestLocalRate('SELECT * FROM commute_data' FROM
'num_cyclists', cdb_crankshaft.CDB_AreasOfInterestLocalRate(
'total_population') As aoi 'SELECT * FROM commute_data'
'num_cyclists',
'total_population') As aoi
JOIN commute_data As c JOIN commute_data As c
ON c.cartodb_id = aoi.rowid; ON c.cartodb_id = aoi.rowid;
``` ```
@ -149,10 +157,13 @@ A table with the following columns.
#### Examples #### Examples
```sql ```sql
SELECT * SELECT
FROM cdb_crankshaft.CDB_AreasOfInterestGlobalRate('SELECT * FROM commute_data', *
'num_cyclists', FROM
'total_population') cdb_crankshaft.CDB_AreasOfInterestGlobalRate(
'SELECT * FROM commute_data',
'num_cyclists',
'total_population')
``` ```
## Hotspot, Coldspot, and Outlier Functions ## Hotspot, Coldspot, and Outlier Functions

8
doc/04_markov.md
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@ -40,8 +40,12 @@ SELECT
m.trend_up, m.trend_up,
m.trend_down, m.trend_down,
m.volatility m.volatility
FROM cdb_crankshaft.CDB_SpatialMarkovTrend('SELECT * FROM nyc_real_estate' FROM
Array['m03y2009','m03y2010','m03y2011','m03y2012','m03y2013','m03y2014','m03y2015','m03y2016']) As m 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 JOIN nyc_real_estate As c
ON c.cartodb_id = m.rowid; ON c.cartodb_id = m.rowid;
``` ```

36
doc/11_kmeans.md
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@ -1,8 +1,8 @@
## K-Means Functions ## 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. 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 #### Example Usage
```sql ```sql
SELECT SELECT
customers.*, customers.*,
km.cluster_no km.cluster_no
FROM cdb_crankshaft.CDB_Kmeans('SELECT * from customers' , 6) km, customers_3 FROM
WHERE customers.cartodb_id = km.cartodb_id 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) ### 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. Function that computes the weighted centroid of a number of clusters by some weight column.
### Arguments ### Arguments
| Name | Type | Description | | 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 | | 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 | | category\_column | TEXT | The name of the column to use as a category |
### Returns ### Returns
A table with the following columns. A table with the following columns.
| Column Name | Type | Description | | Column Name | Type | Description |
|-------------|------|-------------| |-------------|------|-------------|
| the\_geom | GEOMETRY | A point for the weighted cluster center | | 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 ```sql
SELECT ST_TRANSFORM(the_geom, 3857) as the_geom_webmercator, class SELECT
FROM cdb_crankshaft.cdb_weighted_mean('SELECT *, customer_value FROM customers','customer_value','cluster_no') 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
``` ```

8
doc/12_segmentation.md
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@ -3,7 +3,7 @@
### CDB_CreateAndPredictSegment(query TEXT, variable_name TEXT, target_query TEXT) ### 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 #### Arguments
@ -34,12 +34,12 @@ A table with the following columns.
SELECT * from cdb_crankshaft.CDB_CreateAndPredictSegment( SELECT * from cdb_crankshaft.CDB_CreateAndPredictSegment(
'SELECT agg, median_rent::numeric, male_pop::numeric, female_pop::numeric FROM late_night_agg', 'SELECT agg, median_rent::numeric, male_pop::numeric, female_pop::numeric FROM late_night_agg',
'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[]) ### 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 #### Arguments
@ -76,7 +76,7 @@ WITH training As (
FROM late_night_agg), FROM late_night_agg),
target AS ( target AS (
SELECT cdb_crankshaft.CDB_PyAgg(Array[median_rent, male_pop, female_pop]::Numeric[]) As features, 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) SELECT cdb_crankshaft.CDB_CreateAndPredictSegment(training.target, training.features, target.features, target.cartodb_ids)
FROM training, target; FROM training, target;