diff --git a/src/py/crankshaft/crankshaft/clustering/kmeans.py b/src/py/crankshaft/crankshaft/clustering/kmeans.py
index 2477d80..fe6831f 100644
--- a/src/py/crankshaft/crankshaft/clustering/kmeans.py
+++ b/src/py/crankshaft/crankshaft/clustering/kmeans.py
@@ -31,7 +31,7 @@ class Kmeans:
         labels = km.fit_predict(zip(xs, ys))
         return zip(ids, labels)
 
-    def nonspatial(self, subquery, colnames, num_clusters=5,
+    def nonspatial(self, subquery, colnames, no_clusters=5,
                    standardize=True, id_col='cartodb_id'):
         """
             Inputs:
@@ -43,7 +43,7 @@ class Kmeans:
                                                     'petal_width',
                                                     'sepal_length',
                                                     'petal_length']
-            num_clusters (int): number of clusters (greater than zero)
+            no_clusters (int): number of clusters (greater than zero)
             id_col (string): name of the input id_column
 
             Output:
@@ -71,7 +71,7 @@ class Kmeans:
         else:
             cluster_columns = _extract_columns(data, len(colnames))
 
-        kmeans = KMeans(n_clusters=num_clusters,
+        kmeans = KMeans(n_clusters=no_clusters,
                         random_state=0).fit(cluster_columns)
 
         centers = [json.dumps(dict(zip(colnames, c)))