Small cleanups

pandas/core/arrays/datetimelike.py

@@ -401,10 +401,6 @@ def __array__(self, dtype=None):
             return np.array(list(self), dtype=object)
         return self._data
 
-    @property
-    def shape(self):
-        return (len(self),)
-
     @property
     def size(self) -> int:
         """The number of elements in this array."""

pandas/core/arrays/datetimes.py

@@ -265,8 +265,8 @@ class DatetimeArray(dtl.DatetimeLikeArrayMixin,
                              'normalize', 'strftime', 'round', 'floor',
                              'ceil', 'month_name', 'day_name']
 
-    # Needed so that Timestamp.__richcmp__(DateTimeArray) operates pointwise
-    ndim = 1
+    # ndim is inherited from ExtensionArray, must exist to ensure
+    #  Timestamp.__richcmp__(DateTimeArray) operates pointwise
 
     # ensure that operations with numpy arrays defer to our implementation
     __array_priority__ = 1000

pandas/core/dtypes/concat.py

@@ -132,7 +132,7 @@ def is_nonempty(x):
     _contains_period = any(typ.startswith('period') for typ in typs)
 
     if 'category' in typs:
-        # this must be priort to _concat_datetime,
+        # this must be prior to _concat_datetime,
         # to support Categorical + datetime-like
         return _concat_categorical(to_concat, axis=axis)
 

pandas/core/internals/blocks.py

@@ -36,7 +36,6 @@
     Categorical, DatetimeArray, ExtensionArray, PandasDtype, TimedeltaArray)
 from pandas.core.base import PandasObject
 import pandas.core.common as com
-from pandas.core.indexes.datetimes import DatetimeIndex
 from pandas.core.indexing import check_setitem_lengths
 from pandas.core.internals.arrays import extract_array
 import pandas.core.missing as missing
@@ -2091,7 +2090,7 @@ def _astype(self, dtype, **kwargs):
         if is_datetime64tz_dtype(dtype):
             values = self.values
             if getattr(values, 'tz', None) is None:
-                values = DatetimeIndex(values).tz_localize('UTC')
+                values = DatetimeArray(values).tz_localize('UTC')
             values = values.tz_convert(dtype.tz)
             return self.make_block(values)
 
@@ -2420,7 +2419,7 @@ def setitem(self, indexer, value):
         except (ValueError, TypeError):
             newb = make_block(self.values.astype(object),
                               placement=self.mgr_locs,
-                              klass=ObjectBlock,)
+                              klass=ObjectBlock)
             return newb.setitem(indexer, value)
 
     def equals(self, other):

pandas/core/internals/construction.py

@@ -131,8 +131,7 @@ def init_ndarray(values, index, columns, dtype=None, copy=False):
         index, columns = _get_axes(len(values), 1, index, columns)
         return arrays_to_mgr([values], columns, index, columns,
                              dtype=dtype)
-    elif (is_datetime64tz_dtype(values) or
-          is_extension_array_dtype(values)):
+    elif is_extension_array_dtype(values):
         # GH#19157
         if columns is None:
             columns = [0]

pandas/core/internals/managers.py

@@ -15,7 +15,8 @@
     maybe_promote)
 from pandas.core.dtypes.common import (
     _NS_DTYPE, is_datetimelike_v_numeric, is_extension_array_dtype,
-    is_extension_type, is_list_like, is_numeric_v_string_like, is_scalar)
+    is_extension_type, is_list_like, is_numeric_v_string_like, is_scalar,
+    is_sparse)
 import pandas.core.dtypes.concat as _concat
 from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import ABCExtensionArray, ABCSeries
@@ -770,7 +771,6 @@ def _interleave(self):
         Return ndarray from blocks with specified item order
         Items must be contained in the blocks
         """
-        from pandas.core.dtypes.common import is_sparse
         dtype = _interleaved_dtype(self.blocks)
 
         # TODO: https://github.com/pandas-dev/pandas/issues/22791

pandas/io/formats/format.py

@@ -191,6 +191,8 @@ def _chk_truncate(self):
                 series = concat((series.iloc[:row_num],
                                  series.iloc[-row_num:]))
             self.tr_row_num = row_num
+        else:
+            self.tr_row_num = None
         self.tr_series = series
         self.truncate_v = truncate_v
 
@@ -499,6 +501,8 @@ def _chk_truncate(self):
                 frame = concat((frame.iloc[:row_num, :],
                                 frame.iloc[-row_num:, :]))
             self.tr_row_num = row_num
+        else:
+            self.tr_row_num = None
 
         self.tr_frame = frame
         self.truncate_h = truncate_h

pandas/tests/frame/test_repr_info.py

@@ -511,9 +511,11 @@ def test_repr_categorical_dates_periods(self):
 3 2011-01-01 12:00:00-05:00  2011-04
 4 2011-01-01 13:00:00-05:00  2011-05"""
 
-        df = DataFrame({'dt': Categorical(dt), 'p': Categorical(p)})
         assert repr(df) == exp
 
+        df2 = DataFrame({'dt': Categorical(dt), 'p': Categorical(p)})
+        assert repr(df2) == exp
+
     @pytest.mark.parametrize('arg', [np.datetime64, np.timedelta64])
     @pytest.mark.parametrize('box, expected', [
         [Series, '0    NaT\ndtype: object'],

pandas/tests/series/test_api.py

@@ -361,7 +361,8 @@ def test_copy(self):
                 assert np.isnan(s2[0])
                 assert np.isnan(s[0])
 
-        # GH 11794
+    def test_copy_tzaware(self):
+        # GH#11794
         # copy of tz-aware
         expected = Series([Timestamp('2012/01/01', tz='UTC')])
         expected2 = Series([Timestamp('1999/01/01', tz='UTC')])