move whatsnew note, do astype differently

doc/source/whatsnew/v0.24.0.txt

@@ -1124,6 +1124,9 @@ Datetimelike
 - Bug in :class:`PeriodIndex` with attribute ``freq.n`` greater than 1 where adding a :class:`DateOffset` object would return incorrect results (:issue:`23215`)
 - Bug in :class:`Series` that interpreted string indices as lists of characters when setting datetimelike values (:issue:`23451`)
 - Bug in :class:`Timestamp` constructor which would drop the frequency of an input :class:`Timestamp` (:issue:`22311`)
+- Bug in :class:`DatetimeIndex` where calling ``np.array(dtindex, dtype=object)`` would incorrectly return an array of ``long`` objects (:issue:`23524`)
+- Bug in :class:`Index` where passing a timezone-aware :class:`DatetimeIndex` and `dtype=object` would incorrectly raise a ``ValueError`` (:issue:`23524`)
+- Bug in :class:`Index` where calling ``np.array(dtindex, dtype=object)`` on a timezone-naive :class:`DatetimeIndex` would return an array of ``datetime`` objects instead of :class:`Timestamp` objects, potentially losing nanosecond portions of the timestamps (:issue:`23524`)
 
 Timedelta
 ^^^^^^^^^
@@ -1373,6 +1376,3 @@ Other
 - :meth:`~pandas.io.formats.style.Styler.bar` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` and setting clipping range with ``vmin`` and ``vmax`` (:issue:`21548` and :issue:`21526`). ``NaN`` values are also handled properly.
 - Logical operations ``&, |, ^`` between :class:`Series` and :class:`Index` will no longer raise ``ValueError`` (:issue:`22092`)
 - Bug in :meth:`DataFrame.combine_first` in which column types were unexpectedly converted to float (:issue:`20699`)
-- Bug in :class:`Index` where passing a timezone-aware :class:`DatetimeIndex` and `dtype=object` would incorrectly raise a ``ValueError`` (:issue:`23524`)
-- Bug in :class:`DatetimeIndex` where calling ``np.array(dtindex, dtype=object)`` would incorrectly return an array of ``long`` objects (:issue:`23524`)
-- Bug in :class:`Index` where calling ``np.array(dtindex, dtype=object)`` on a timezone-naive :class:`DatetimeIndex` would return an array of ``datetime`` objects instead of :class:`Timestamp` objects, potentially losing nanosecond portions of the timestamps (:issue:`23524`)

pandas/core/indexes/base.py

@@ -307,8 +307,10 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
                 #  will raise in the where `data` is already tz-aware.  So
                 #  we leave it out of this step and cast to object-dtype after
                 #  the DatetimeIndex construction.
-                result = DatetimeIndex(data, copy=copy, name=name, **kwargs)
-                return Index(list(result), dtype=_o_dtype)
+                # Note we can pass copy=False because the .astype below
+                #  will always make a copy
+                result = DatetimeIndex(data, copy=False, name=name, **kwargs)
+                return result.astype(object)
             else:
                 result = DatetimeIndex(data, copy=copy, name=name,
                                        dtype=dtype, **kwargs)