diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index b90833bda82b5..5174f25e0da06 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2,7 +2,7 @@
 from __future__ import annotations
 
 import collections
-from datetime import timedelta
+import datetime as dt
 import gc
 import json
 import operator
@@ -133,12 +133,12 @@
 from pandas.core import (
     algorithms as algos,
     arraylike,
-    common as com,
     indexing,
     missing,
     nanops,
     sample,
 )
+from pandas.core import common  # noqa: PDF018
 from pandas.core.array_algos.replace import should_use_regex
 from pandas.core.arrays import ExtensionArray
 from pandas.core.base import PandasObject
@@ -1009,7 +1009,7 @@ def _rename(
                 continue
 
             ax = self._get_axis(axis_no)
-            f = com.get_rename_function(replacements)
+            f = common.get_rename_function(replacements)
 
             if level is not None:
                 level = ax._get_level_number(level)
@@ -1240,7 +1240,7 @@ class  name
                 if non_mapper:
                     newnames = v
                 else:
-                    f = com.get_rename_function(v)
+                    f = common.get_rename_function(v)
                     curnames = self._get_axis(axis).names
                     newnames = [f(name) for name in curnames]
                 result._set_axis_name(newnames, axis=axis, inplace=True)
@@ -1826,7 +1826,7 @@ def _drop_labels_or_levels(self, keys, axis: AxisInt = 0):
         axis = self._get_axis_number(axis)
 
         # Validate keys
-        keys = com.maybe_make_list(keys)
+        keys = common.maybe_make_list(keys)
         invalid_keys = [
             k for k in keys if not self._is_label_or_level_reference(k, axis=axis)
         ]
@@ -4445,7 +4445,7 @@ def _drop_axis(
         # Case for non-unique axis
         else:
             is_tuple_labels = is_nested_list_like(labels) or isinstance(labels, tuple)
-            labels = ensure_object(com.index_labels_to_array(labels))
+            labels = ensure_object(common.index_labels_to_array(labels))
             if level is not None:
                 if not isinstance(axis, MultiIndex):
                     raise AssertionError("axis must be a MultiIndex")
@@ -5236,7 +5236,7 @@ def _reindex_axes(
     def _needs_reindex_multi(self, axes, method, level) -> bool_t:
         """Check if we do need a multi reindex."""
         return (
-            (com.count_not_none(*axes.values()) == self._AXIS_LEN)
+            (common.count_not_none(*axes.values()) == self._AXIS_LEN)
             and method is None
             and level is None
             and not self._is_mixed_type
@@ -5359,7 +5359,7 @@ def filter(
                  one  two  three
         rabbit    4    5      6
         """
-        nkw = com.count_not_none(items, like, regex)
+        nkw = common.count_not_none(items, like, regex)
         if nkw > 1:
             raise TypeError(
                 "Keyword arguments `items`, `like`, or `regex` "
@@ -5684,7 +5684,7 @@ def sample(
         obj_len = self.shape[axis]
 
         # Process random_state argument
-        rs = com.random_state(random_state)
+        rs = common.random_state(random_state)
 
         size = sample.process_sampling_size(n, frac, replace)
         if size is None:
@@ -5760,7 +5760,7 @@ def pipe(
         ...    .pipe((func, 'arg2'), arg1=a, arg3=c)
         ...  )  # doctest: +SKIP
         """
-        return com.pipe(self, func, *args, **kwargs)
+        return common.pipe(self, func, *args, **kwargs)
 
     # ----------------------------------------------------------------------
     # Attribute access
@@ -9445,7 +9445,7 @@ def _where(
             axis = self._get_axis_number(axis)
 
         # align the cond to same shape as myself
-        cond = com.apply_if_callable(cond, self)
+        cond = common.apply_if_callable(cond, self)
         if isinstance(cond, NDFrame):
             cond, _ = cond.align(self, join="right", broadcast_axis=1, copy=False)
         else:
@@ -9467,9 +9467,9 @@ def _where(
                 if not is_bool_dtype(cond):
                     raise ValueError(msg.format(dtype=cond.dtype))
             else:
-                for dt in cond.dtypes:
-                    if not is_bool_dtype(dt):
-                        raise ValueError(msg.format(dtype=dt))
+                for _dt in cond.dtypes:
+                    if not is_bool_dtype(_dt):
+                        raise ValueError(msg.format(dtype=_dt))
         else:
             # GH#21947 we have an empty DataFrame/Series, could be object-dtype
             cond = cond.astype(bool)
@@ -9747,7 +9747,7 @@ def where(
         3  True  True
         4  True  True
         """
-        other = com.apply_if_callable(other, self)
+        other = common.apply_if_callable(other, self)
         return self._where(cond, other, inplace, axis, level)
 
     @overload
@@ -9805,7 +9805,7 @@ def mask(
     ) -> NDFrameT | None:
 
         inplace = validate_bool_kwarg(inplace, "inplace")
-        cond = com.apply_if_callable(cond, self)
+        cond = common.apply_if_callable(cond, self)
 
         # see gh-21891
         if not hasattr(cond, "__invert__"):
@@ -10317,7 +10317,7 @@ def tz_localize(
         """
         nonexistent_options = ("raise", "NaT", "shift_forward", "shift_backward")
         if nonexistent not in nonexistent_options and not isinstance(
-            nonexistent, timedelta
+            nonexistent, dt.timedelta
         ):
             raise ValueError(
                 "The nonexistent argument must be one of 'raise', "
@@ -11470,7 +11470,7 @@ def min(
     @doc(Rolling)
     def rolling(
         self,
-        window: int | timedelta | str | BaseOffset | BaseIndexer,
+        window: int | dt.timedelta | str | BaseOffset | BaseIndexer,
         min_periods: int | None = None,
         center: bool_t = False,
         win_type: str | None = None,