fixup

Author: TomAugspurger

doc/source/whatsnew/v0.24.0.rst

@@ -1273,7 +1273,7 @@ Converting Timezone-Aware Series and Index to NumPy Arrays
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 The conversion from a :class:`Series` or :class:`Index` with timezone-aware
-datetime data will changing to preserve timezones by default (:issue:`23569`).
+datetime data will change to preserve timezones by default (:issue:`23569`).
 
 NumPy doesn't have a dedicated dtype for timezone-aware datetimes.
 In the past, converting a :class:`Series` or :class:`DatetimeIndex` with
@@ -1292,7 +1292,7 @@ timezone attached
    ser = pd.Series(pd.date_range('2000', periods=2, tz="CET"))
    ser
 
-The default behavior renames the same, but issues a warning
+The default behavior remains the same, but issues a warning
 
 .. code-block:: python
 

pandas/core/groupby/groupby.py

@@ -26,8 +26,7 @@ class providing the base-class of operations.
 
 from pandas.core.dtypes.cast import maybe_downcast_to_dtype
 from pandas.core.dtypes.common import (
-    _NS_DTYPE, ensure_float, is_datetime64tz_dtype, is_extension_array_dtype,
-    is_numeric_dtype, is_scalar)
+    ensure_float, is_extension_array_dtype, is_numeric_dtype, is_scalar)
 from pandas.core.dtypes.missing import isna, notna
 
 import pandas.core.algorithms as algorithms
@@ -1270,18 +1269,10 @@ def f(self, **kwargs):
             return f
 
         def first_compat(x, axis=0):
-            # This is a bit strange.
-            # We only hit this block when grouping a DatetimeTZBlock *and*
-            # a categorical. Something strange going on with first for
-            # categorical dta.
-            if is_datetime64tz_dtype(x.dtype):
-                dtype = _NS_DTYPE
-            else:
-                dtype = None
 
             def first(x):
+                x = x.to_numpy()
 
-                x = np.asarray(x, dtype=dtype)
                 x = x[notna(x)]
                 if len(x) == 0:
                     return np.nan
@@ -1293,18 +1284,9 @@ def first(x):
                 return first(x)
 
         def last_compat(x, axis=0):
-            # This is a bit strange.
-            # We only hit this block when grouping a DatetimeTZBlock *and*
-            # a categorical. Something strange going on with first for
-            # categorical dta.
-            if is_datetime64tz_dtype(x.dtype):
-                dtype = _NS_DTYPE
-            else:
-                dtype = None
 
             def last(x):
-
-                x = np.asarray(x, dtype=dtype)
+                x = x.to_numpy()
                 x = x[notna(x)]
                 if len(x) == 0:
                     return np.nan

pandas/core/indexes/datetimes.py

@@ -340,8 +340,8 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
     # --------------------------------------------------------------------
 
     def __array__(self, dtype=None):
-        if dtype is None and isinstance(self._data, DatetimeArray)\
-                and getattr(self.dtype, 'tz', None):
+        if (dtype is None and isinstance(self._data, DatetimeArray)
+                and getattr(self.dtype, 'tz', None)):
             msg = (
                 "Converting timezone-aware DatetimeArray to timezone-naive "
                 "ndarray with 'datetime64[ns]' dtype. In the future, this "