CLN: assorted cleanups (#30575)

Author: jbrockmendel

doc/source/whatsnew/v1.0.0.rst

@@ -794,6 +794,7 @@ Datetimelike
 - Bug in :class:`DatetimeIndex` addition when adding a non-optimized :class:`DateOffset` incorrectly dropping timezone information (:issue:`30336`)
 - Bug in :meth:`DataFrame.drop` where attempting to drop non-existent values from a DatetimeIndex would yield a confusing error message (:issue:`30399`)
 - Bug in :meth:`DataFrame.append` would remove the timezone-awareness of new data (:issue:`30238`)
+- Bug in :meth:`Series.cummin` and :meth:`Series.cummax` with timezone-aware dtype incorrectly dropping its timezone (:issue:`15553`)
 - Bug in :class:`DatetimeArray`, :class:`TimedeltaArray`, and :class:`PeriodArray` where inplace addition and subtraction did not actually operate inplace (:issue:`24115`)
 
 Timedelta

pandas/_config/config.py

@@ -197,7 +197,7 @@ def __setattr__(self, key, val):
         else:
             raise OptionError("You can only set the value of existing options")
 
-    def __getattr__(self, key):
+    def __getattr__(self, key: str):
         prefix = object.__getattribute__(self, "prefix")
         if prefix:
             prefix += "."

pandas/compat/numpy/function.py

@@ -169,13 +169,6 @@ def validate_clip_with_axis(axis, args, kwargs):
     return axis
 
 
-COMPRESS_DEFAULTS: "OrderedDict[str, Any]" = OrderedDict()
-COMPRESS_DEFAULTS["axis"] = None
-COMPRESS_DEFAULTS["out"] = None
-validate_compress = CompatValidator(
-    COMPRESS_DEFAULTS, fname="compress", method="both", max_fname_arg_count=1
-)
-
 CUM_FUNC_DEFAULTS: "OrderedDict[str, Any]" = OrderedDict()
 CUM_FUNC_DEFAULTS["dtype"] = None
 CUM_FUNC_DEFAULTS["out"] = None

pandas/core/generic.py

@@ -11120,6 +11120,7 @@ def cum_func(self, axis=None, skipna=True, *args, **kwargs):
         def na_accum_func(blk_values):
             # We will be applying this function to block values
             if blk_values.dtype.kind in ["m", "M"]:
+                # GH#30460, GH#29058
                 # numpy 1.18 started sorting NaTs at the end instead of beginning,
                 #  so we need to work around to maintain backwards-consistency.
                 orig_dtype = blk_values.dtype

pandas/core/groupby/groupby.py

@@ -325,7 +325,7 @@ def f(self):
         f.__name__ = "plot"
         return self._groupby.apply(f)
 
-    def __getattr__(self, name):
+    def __getattr__(self, name: str):
         def attr(*args, **kwargs):
             def f(self):
                 return getattr(self.plot, name)(*args, **kwargs)
@@ -570,7 +570,7 @@ def _set_result_index_ordered(self, result):
     def _dir_additions(self):
         return self.obj._dir_additions() | self._apply_whitelist
 
-    def __getattr__(self, attr):
+    def __getattr__(self, attr: str):
         if attr in self._internal_names_set:
             return object.__getattribute__(self, attr)
         if attr in self.obj:

pandas/core/resample.py

@@ -96,7 +96,7 @@ def __str__(self) -> str:
         )
         return f"{type(self).__name__} [{', '.join(attrs)}]"
 
-    def __getattr__(self, attr):
+    def __getattr__(self, attr: str):
         if attr in self._internal_names_set:
             return object.__getattribute__(self, attr)
         if attr in self._attributes:
@@ -131,7 +131,7 @@ def ax(self):
         return self.groupby.ax
 
     @property
-    def _typ(self):
+    def _typ(self) -> str:
         """
         Masquerade for compat as a Series or a DataFrame.
         """
@@ -140,7 +140,7 @@ def _typ(self):
         return "dataframe"
 
     @property
-    def _from_selection(self):
+    def _from_selection(self) -> bool:
         """
         Is the resampling from a DataFrame column or MultiIndex level.
         """
@@ -316,7 +316,7 @@ def _downsample(self, f):
     def _upsample(self, f, limit=None, fill_value=None):
         raise AbstractMethodError(self)
 
-    def _gotitem(self, key, ndim, subset=None):
+    def _gotitem(self, key, ndim: int, subset=None):
         """
         Sub-classes to define. Return a sliced object.
 
@@ -1407,7 +1407,7 @@ def _get_resampler(self, obj, kind=None):
             f"but got an instance of '{type(ax).__name__}'"
         )
 
-    def _get_grouper(self, obj, validate=True):
+    def _get_grouper(self, obj, validate: bool = True):
         # create the resampler and return our binner
         r = self._get_resampler(obj)
         r._set_binner()

pandas/core/reshape/concat.py

@@ -472,9 +472,9 @@ def _get_result_dim(self) -> int:
         else:
             return self.objs[0].ndim
 
-    def _get_new_axes(self):
+    def _get_new_axes(self) -> List[Index]:
         ndim = self._get_result_dim()
-        new_axes = [None] * ndim
+        new_axes: List = [None] * ndim
 
         for i in range(ndim):
             if i == self.axis:

pandas/core/window/rolling.py

@@ -184,7 +184,7 @@ def _gotitem(self, key, ndim, subset=None):
                 self._selection = key
         return self
 
-    def __getattr__(self, attr):
+    def __getattr__(self, attr: str):
         if attr in self._internal_names_set:
             return object.__getattribute__(self, attr)
         if attr in self.obj:

pandas/tests/indexes/datetimes/test_constructors.py

@@ -711,7 +711,6 @@ def test_constructor_timestamp_near_dst(self):
         expected = DatetimeIndex([ts[0].to_pydatetime(), ts[1].to_pydatetime()])
         tm.assert_index_equal(result, expected)
 
-    # TODO(GH-24559): Remove the xfail for the tz-aware case.
     @pytest.mark.parametrize("klass", [Index, DatetimeIndex])
     @pytest.mark.parametrize("box", [np.array, partial(np.array, dtype=object), list])
     @pytest.mark.parametrize(

pandas/util/_depr_module.py

@@ -46,7 +46,7 @@ def __repr__(self) -> str:
 
     __str__ = __repr__
 
-    def __getattr__(self, name):
+    def __getattr__(self, name: str):
         if name in self.self_dir:
             return object.__getattribute__(self, name)