review edits and fix issue

doc/source/whatsnew/v0.23.0.txt

@@ -288,6 +288,7 @@ Conversion
 - Bug in :class:`Series` constructor with an int or float list where specifying ``dtype=str``, ``dtype='str'`` or ``dtype='U'`` failed to convert the data elements to strings (:issue:`16605`)
 - Bug in :class:`Timestamp` where comparison with an array of ``Timestamp`` objects would result in a ``RecursionError`` (:issue:`15183`)
 - Bug in :class:`WeekOfMonth` and class:`Week` where addition and subtraction did not roll correctly (:issue:`18510`,:issue:`18672`,:issue:`18864`)
+- Bug in :meth:`DatetimeIndex.astype` when converting between timezone aware dtypes, and converting from timezone aware to naive (:issue:`18951`)
 
 
 Indexing

pandas/core/indexes/base.py

@@ -1065,7 +1065,9 @@ def _to_embed(self, keep_tz=False, dtype=None):
 
     @Appender(_index_shared_docs['astype'])
     def astype(self, dtype, copy=True):
-        if is_categorical_dtype(dtype):
+        if is_dtype_equal(self.dtype, dtype):
+            return self.copy() if copy else self
+        elif is_categorical_dtype(dtype):
             from .category import CategoricalIndex
             return CategoricalIndex(self.values, name=self.name, dtype=dtype,
                                     copy=copy)

pandas/core/indexes/datetimelike.py

@@ -876,7 +876,10 @@ def astype(self, dtype, copy=True):
         elif is_integer_dtype(dtype):
             return Index(self.values.astype('i8', copy=copy), name=self.name,
                          dtype='i8')
-        elif is_float_dtype(dtype) or is_datetime_or_timedelta_dtype(dtype):
+        elif (is_datetime_or_timedelta_dtype(dtype) and
+              not is_dtype_equal(self.dtype, dtype)) or is_float_dtype(dtype):
+            # disallow conversion between datetime/timedelta,
+            # and conversions for any datetimelike to float
             msg = 'Cannot cast {name} to dtype {dtype}'
             raise TypeError(msg.format(name=type(self).__name__, dtype=dtype))
         return super(DatetimeIndexOpsMixin, self).astype(dtype, copy=copy)

pandas/core/indexes/datetimes.py

@@ -905,10 +905,13 @@ def _format_native_types(self, na_rep='NaT', date_format=None, **kwargs):
     @Appender(_index_shared_docs['astype'])
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
-        if is_datetime64_ns_dtype(dtype):
-            if self.tz is not None:
-                return self.tz_convert('UTC').tz_localize(None)
-            return self.copy() if copy else self
+        if (is_datetime64_ns_dtype(dtype) and
+                not is_dtype_equal(dtype, self.dtype)):
+            # GH 18951: datetime64_ns dtype but not equal means different tz
+            new_tz = getattr(dtype, 'tz', None)
+            if getattr(self.dtype, 'tz', None) is None:
+                return self.tz_localize(new_tz)
+            return self.tz_convert(new_tz)
         elif is_period_dtype(dtype):
             return self.to_period(freq=dtype.freq)
         return super(DatetimeIndex, self).astype(dtype, copy=copy)

pandas/core/indexes/timedeltas.py

@@ -480,9 +480,7 @@ def to_pytimedelta(self):
     @Appender(_index_shared_docs['astype'])
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
-        if is_timedelta64_ns_dtype(dtype):
-            return self.copy() if copy else self
-        elif is_timedelta64_dtype(dtype):
+        if is_timedelta64_dtype(dtype) and not is_timedelta64_ns_dtype(dtype):
             # return an index (essentially this is division)
             result = self.values.astype(dtype, copy=copy)
             if self.hasnans:

pandas/tests/indexes/datetimes/test_astype.py

@@ -57,6 +57,18 @@ def test_astype_with_tz(self):
                           dtype=object)
         tm.assert_series_equal(result, expected)
 
+        # GH 18951: tz-aware to tz-aware
+        idx = date_range('20170101', periods=4, tz='US/Pacific')
+        result = idx.astype('datetime64[ns, US/Eastern]')
+        expected = date_range('20170101 03:00:00', periods=4, tz='US/Eastern')
+        tm.assert_index_equal(result, expected)
+
+        # GH 18951: tz-naive to tz-aware
+        idx = date_range('20170101', periods=4)
+        result = idx.astype('datetime64[ns, US/Eastern]')
+        expected = date_range('20170101', periods=4, tz='US/Eastern')
+        tm.assert_index_equal(result, expected)
+
     def test_astype_str_compat(self):
         # GH 13149, GH 13209
         # verify that we are returing NaT as a string (and not unicode)

pandas/tests/indexes/test_range.py

@@ -711,7 +711,7 @@ def test_nbytes(self):
 
         # memory savings vs int index
         i = RangeIndex(0, 1000)
-        assert i.nbytes < i.astype(int).nbytes / 10
+        assert i.nbytes < i._int64index.nbytes / 10
 
         # constant memory usage
         i2 = RangeIndex(0, 10)