API: Return Index from DatetimeIndex/PeriodIndex.strftime

Author: reidy-p

doc/source/whatsnew/v0.23.0.txt

@@ -711,6 +711,7 @@ Other API Changes
 - ``Categorical.fillna`` now validates its ``value`` and ``method`` keyword arguments. It now raises when both or none are specified, matching the behavior of :meth:`Series.fillna` (:issue:`19682`)
 - ``pd.to_datetime('today')`` now returns a datetime, consistent with ``pd.Timestamp('today')``; previously ``pd.to_datetime('today')`` returned a ``.normalized()`` datetime (:issue:`19935`)
 - :func:`Series.str.replace` now takes an optional `regex` keyword which, when set to ``False``, uses literal string replacement rather than regex replacement (:issue:`16808`)
+- ``DatetimeIndex.strftime`` and ``PeriodIndex.strftime`` now return an ``Index`` instead of a numpy array to be consistent with similar accessors (:issue:`20127`)
 
 .. _whatsnew_0230.deprecations:
 

pandas/core/indexes/datetimelike.py

@@ -58,10 +58,10 @@ class DatelikeOps(object):
     """ common ops for DatetimeIndex/PeriodIndex, but not TimedeltaIndex """
 
     def strftime(self, date_format):
-        return np.asarray(self.format(date_format=date_format),
-                          dtype=compat.text_type)
+        return Index(self.format(date_format=date_format),
+                     dtype=compat.text_type)
     strftime.__doc__ = """
-    Return an array of formatted strings specified by date_format, which
+    Return an Index of formatted strings specified by date_format, which
     supports the same string format as the python standard library. Details
     of the string format can be found in `python string format doc <{0}>`__
 
@@ -72,7 +72,7 @@ def strftime(self, date_format):
 
     Returns
     -------
-    ndarray of formatted strings
+    Index of formatted strings
     """.format("https://docs.python.org/3/library/datetime.html"
                "#strftime-and-strptime-behavior")
 

pandas/tests/series/test_datetime_values.py

@@ -355,16 +355,16 @@ def test_strftime(self):
         datetime_index = date_range('20150301', periods=5)
         result = datetime_index.strftime("%Y/%m/%d")
 
-        expected = np.array(['2015/03/01', '2015/03/02', '2015/03/03',
-                             '2015/03/04', '2015/03/05'], dtype=np.object_)
+        expected = Index(['2015/03/01', '2015/03/02', '2015/03/03',
+                          '2015/03/04', '2015/03/05'], dtype=np.object_)
         # dtype may be S10 or U10 depending on python version
-        tm.assert_numpy_array_equal(result, expected, check_dtype=False)
+        tm.assert_index_equal(result, expected)
 
         period_index = period_range('20150301', periods=5)
         result = period_index.strftime("%Y/%m/%d")
-        expected = np.array(['2015/03/01', '2015/03/02', '2015/03/03',
-                             '2015/03/04', '2015/03/05'], dtype='=U10')
-        tm.assert_numpy_array_equal(result, expected)
+        expected = Index(['2015/03/01', '2015/03/02', '2015/03/03',
+                          '2015/03/04', '2015/03/05'], dtype='=U10')
+        tm.assert_index_equal(result, expected)
 
         s = Series([datetime(2013, 1, 1, 2, 32, 59), datetime(2013, 1, 2, 14,
                                                               32, 1)])