added docstring to new methods. Merged all datetime tests into one test, updated whatsnew

Author: aileronajay

doc/source/whatsnew/v0.20.0.txt

@@ -50,6 +50,7 @@ Other enhancements
 
 - ``pd.read_excel`` now preserves sheet order when using ``sheetname=None`` (:issue:`9930`)
 
+ENH: support cut/qcut for datetime/timedelta (GH14714)
 
 .. _whatsnew_0200.api_breaking:
 

pandas/tools/tests/test_tile.py

@@ -286,6 +286,7 @@ def test_single_bin(self):
 
     def test_datetime_cut(self):
         # GH 14714
+        # testing for time data to be present as series
         data = to_datetime(Series(['2013-01-01', '2013-01-02', '2013-01-03']))
         result, bins = cut(data, 3, retbins=True)
         expected = Series(['(2012-12-31 23:57:07.200000, 2013-01-01 16:00:00]',
@@ -294,37 +295,23 @@ def test_datetime_cut(self):
                           ).astype("category", ordered=True)
         tm.assert_series_equal(result, expected)
 
-    def test_datetime_list_cut(self):
-        # GH 14714
+        # testing for time data to be present as list
         data = [np.datetime64('2013-01-01'), np.datetime64('2013-01-02'),
                 np.datetime64('2013-01-03')]
         result, bins = cut(data, 3, retbins=True)
-        expected = Series(['(2012-12-31 23:57:07.200000, 2013-01-01 16:00:00]',
-                          '(2013-01-01 16:00:00, 2013-01-02 08:00:00]',
-                           '(2013-01-02 08:00:00, 2013-01-03 00:00:00]'],
-                          ).astype("category", ordered=True)
         tm.assert_series_equal(Series(result), expected)
 
-    def test_datetime_ndarray_cut(self):
-        # GH 14714
+        # testing for time data to be present as ndarray
+
         data = np.array([np.datetime64('2013-01-01'), 
                         np.datetime64('2013-01-02'),
                         np.datetime64('2013-01-03')])
         result, bins = cut(data, 3, retbins=True)
-        expected = Series(['(2012-12-31 23:57:07.200000, 2013-01-01 16:00:00]',
-                          '(2013-01-01 16:00:00, 2013-01-02 08:00:00]',
-                           '(2013-01-02 08:00:00, 2013-01-03 00:00:00]'],
-                          ).astype("category", ordered=True)
         tm.assert_series_equal(Series(result), expected)
 
-    def test_datetime_index_cut(self):
-        # GH 14714
+        # testing for time data to be present as datetime index
         data = DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03'])
         result, bins = cut(data, 3, retbins=True)
-        expected = Series(['(2012-12-31 23:57:07.200000, 2013-01-01 16:00:00]',
-                          '(2013-01-01 16:00:00, 2013-01-02 08:00:00]',
-                           '(2013-01-02 08:00:00, 2013-01-03 00:00:00]'],
-                          ).astype("category", ordered=True)
         tm.assert_series_equal(Series(result), expected)
 
 

pandas/tools/tile.py

@@ -311,6 +311,11 @@ def _trim_zeros(x):
 
 
 def _coerce_to_type(x):
+    '''
+    if the passed data is of datetime/timedelta type,
+    this method converts it to integer so that cut method can
+    handle it
+    '''
     dtype = None
     original = x
     if is_timedelta64_dtype(x):
@@ -324,6 +329,11 @@ def _coerce_to_type(x):
 
 
 def _preprocess_for_cut(x):
+    '''
+    handles preprocessing for cut where we convert passed
+    input to array, strip the index information and store it
+    seperately
+    '''
     x_is_series = isinstance(x, Series)
     series_index = None
 
@@ -339,6 +349,11 @@ def _preprocess_for_cut(x):
 
 
 def _postprocess_for_cut(fac, bins, retbins, x_is_series, series_index, name):
+    '''
+    handles post processing for the cut method where
+    we combine the index information if the originally passed
+    datatype was a series
+    '''
     if x_is_series:
         fac = Series(fac, index=series_index, name=name)