BUG: DatetimeIndex._data should return an ndarray

Author: reidy-p

doc/source/whatsnew/v0.23.0.txt

@@ -996,6 +996,7 @@ Other API Changes
 - :func:`DataFrame.to_dict` with ``orient='index'`` no longer casts int columns to float for a DataFrame with only int and float columns (:issue:`18580`)
 - A user-defined-function that is passed to :func:`Series.rolling().aggregate() <pandas.core.window.Rolling.aggregate>`, :func:`DataFrame.rolling().aggregate() <pandas.core.window.Rolling.aggregate>`, or its expanding cousins, will now *always* be passed a ``Series``, rather than a ``np.array``; ``.apply()`` only has the ``raw`` keyword, see :ref:`here <whatsnew_0230.enhancements.window_raw>`. This is consistent with the signatures of ``.aggregate()`` across pandas (:issue:`20584`)
 - Rolling and Expanding types raise ``NotImplementedError`` upon iteration (:issue:`11704`).
+- ``DatetimeIndex._data`` now returns a numpy array in all cases (:issue:`20810`)
 
 .. _whatsnew_0230.deprecations:
 

pandas/core/indexes/datetimes.py

@@ -619,6 +619,9 @@ def _simple_new(cls, values, name=None, freq=None, tz=None,
         if we are passed a non-dtype compat, then coerce using the constructor
         """
 
+        if isinstance(values, DatetimeIndex):
+            values = values.values
+
         if getattr(values, 'dtype', None) is None:
             # empty, but with dtype compat
             if values is None: