diff --git a/src/pg/sql/11_kmeans.sql b/src/pg/sql/11_kmeans.sql
index 2db57e0..6a9d1a9 100644
--- a/src/pg/sql/11_kmeans.sql
+++ b/src/pg/sql/11_kmeans.sql
@@ -11,12 +11,18 @@ $$ LANGUAGE plpythonu;
 -- Non-spatial k-means clustering
 -- query: sql query to retrieve all the needed data
 
-CREATE OR REPLACE FUNCTION CDB_KMeansNonspatial(query TEXT, colnames TEXT[], num_clusters INTEGER, id_col TEXT DEFAULT 'cartodb_id')
+CREATE OR REPLACE FUNCTION CDB_KMeansNonspatial(
+  query TEXT,
+  colnames TEXT[],
+  num_clusters INTEGER,
+  id_col TEXT DEFAULT 'cartodb_id',
+  standarize BOOLEAN DEFAULT true
+)
 RETURNS TABLE(cluster_label text, cluster_center text, rowid bigint) AS $$
 
-from crankshaft.clustering import kmeans_nonspatial
-return kmeans_nonspatial(query, colnames, num_clusters, id_col)
-
+    from crankshaft.clustering import kmeans_nonspatial
+    return kmeans_nonspatial(query, colnames, num_clusters,
+                             id_col, standarize)
 $$ LANGUAGE plpythonu;
 
 
diff --git a/src/py/crankshaft/crankshaft/clustering/kmeans.py b/src/py/crankshaft/crankshaft/clustering/kmeans.py
index df024a1..6e972e5 100644
--- a/src/py/crankshaft/crankshaft/clustering/kmeans.py
+++ b/src/py/crankshaft/crankshaft/clustering/kmeans.py
@@ -62,7 +62,7 @@ def kmeans_nonspatial(query, colnames, num_clusters=5,
         cluster_columns = _scale_data(
           _extract_columns(db_resp, id_col=out_id_colname))
     else:
-        cluster_columns = _extract_columns(db_resp)
+        cluster_columns = _extract_columns(db_resp, id_col=out_id_colname)
 
     # TODO: decide on optimal parameters for most cases
     #       Are there ways of deciding parameters based on inputs?