address comments

glemaitre · glemaitre · commit eecb39aa4198 · 2018-06-26T18:18:51.000+02:00
diff --git a/doc/whats_new/v0.20.rst b/doc/whats_new/v0.20.rst
@@ -260,31 +260,28 @@ Preprocessing
   classes found which are ignored.
   :issue:`10913` by :user:`Rodrigo Agundez <rragundez>`.
 
-- :class:`preprocessing.QuantileTransformer` handles and ignores NaN values.
-  :issue:`10404` by :user:`Guillaume Lemaitre <glemaitre>`.
-
-- Updated :class:`preprocessing.MinMaxScaler` and
-  :func:`preprocessing.minmax_scale` to pass through NaN values.
-  :issue:`10404` and :issue:`11243` by :user:`Lucija Gregov <LucijaGregov>` and
+- NaN values are ignored and handled in the following preprocessing methods:
+  :class:`preprocessing.MaxAbsScaler`,
+  :class:`preprocessing.MinMaxScaler`,
+  :class:`preprocessing.RobustScaler`,
+  :class:`preprocessing.StandardScaler`,
+  :class:`preprocessing.PowerTransformer`,
+  :class:`preprocessing.QuantileTransformer` classes and
+  :func:`preprocessing.maxabs_scale`,
+  :func:`preprocessing.minmax_scale`,
+  :func:`preprocessing.robust_scale`,
+  :func:`preprocessing.scale`,
+  :func:`preprocessing.power_transform`,
+  :func:`preprocessing.quantile_transform` functions respectively addressed in
+  issues :issue:`11011`, :issue:`11005`, :issue:`11308`, :issue:`11206`,
+  :issue:`11306`, and :issue:`10437`.
+  By :user:`Lucija Gregov <LucijaGregov>` and
   :user:`Guillaume Lemaitre <glemaitre>`.
 
-- :class:`preprocessing.StandardScaler` and :func:`preprocessing.scale`
-  ignore and pass-through NaN values.
-  :issue:`11206` by :user:`Guillaume Lemaitre <glemaitre>`.
-
-- :class:`preprocessing.MaxAbsScaler` and :func:`preprocessing.maxabs_scale`
-  handles and ignores NaN values.
-  :issue:`11011` by `Lucija Gregov <LucihaGregov>` and
-  :user:`Guillaume Lemaitre <glemaitre>`
-
-- :class:`preprocessing.PowerTransformer` and
-  :func:`preprocessing.power_transform` ignore and pass-through NaN values.
-  :issue:`11306` by :user:`Guillaume Lemaitre <glemaitre>`.
 - :class:`preprocessing.RobustScaler` and :func:`preprocessing.robust_scale`
-  ignore and pass-through NaN values. In addition, the scaler can now be fitted
-  on sparse matrices.
+  can be fitted using sparse matrices.
   :issue:`11308` by :user:`Guillaume Lemaitre <glemaitre>`.
-
+  
 Model evaluation and meta-estimators
 
 - A scorer based on :func:`metrics.brier_score_loss` is also available.
diff --git a/sklearn/preprocessing/data.py b/sklearn/preprocessing/data.py
@@ -1137,7 +1137,7 @@ def fit(self, X, y=None):
 
             quantiles = np.transpose(quantiles)
 
-            self.scale_ = (quantiles[1] - quantiles[0])
+            self.scale_ = quantiles[1] - quantiles[0]
             self.scale_ = _handle_zeros_in_scale(self.scale_, copy=False)
         else:
             self.scale_ = None
