crankshaft/doc/11_kmeans.md

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## K-Means Functions
### 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
the number of the cluster each point in the input was assigend to.
#### Arguments
| Name | Type | Description |
|------|------|-------------|
| subquery | TEXT | SQL query that exposes the data to be analyzed (e.g., `SELECT * FROM interesting_table`). This query must have the geometry column name `the_geom` and id column name `cartodb_id` unless otherwise specified in the input arguments |
| no\_clusters | INTEGER | The number of clusters to try and find |
#### Returns
A table with the following columns.
| Column Name | Type | Description |
|-------------|------|-------------|
| cartodb\_id | INTEGER | The CartoDB id of the row in the input table.|
| cluster\_no | INTEGER | The cluster that this point belongs to. |
#### 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
```
### 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
| Name | Type | Description |
|------|------|-------------|
| subquery | TEXT | SQL query that exposes the data to be analyzed (e.g., `SELECT * FROM interesting_table`). This query must have the geometry column and the columns specified as the weight and category columns|
| 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
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 |
### 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')
```