Normalized whitespace in OrdinalEncoder doc string

baluyotraf · baluyotraf · commit b7decc055cd1 · 2019-03-26T22:09:00.000+08:00
diff --git a/doc/modules/preprocessing.rst b/doc/modules/preprocessing.rst
@@ -481,7 +481,7 @@ new feature of integers (0 to n_categories - 1)::
 
     >>> enc = preprocessing.OrdinalEncoder()
     >>> X = [['male', 'from US', 'uses Safari'], ['female', 'from Europe', 'uses Firefox']]
-    >>> enc.fit(X)  # doctest: +ELLIPSIS
+    >>> enc.fit(X)  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
     OrdinalEncoder(categories='auto', dtype=<... 'numpy.float64'>,
         missing_values=nan)
     >>> enc.transform([['female', 'from US', 'uses Safari']])
diff --git a/sklearn/preprocessing/_encoders.py b/sklearn/preprocessing/_encoders.py
@@ -964,6 +964,7 @@ class OrdinalEncoder(_BaseEncoder):
     >>> X = [['Male', 1], ['Female', 3], ['Female', 2]]
     >>> enc.fit(X)
     ... # doctest: +ELLIPSIS
+    ... # doctest: +NORMALIZE_WHITESPACE
     OrdinalEncoder(categories='auto', dtype=<... 'numpy.float64'>,
         missing_values=nan)
 
