fix mypy errors

Author: topper-123

pandas/core/frame.py

@@ -87,12 +87,13 @@
 from pandas.core.dtypes.missing import isna, notna
 
 from pandas._typing import Axes, Dtype, FilePathOrBuffer
-from pandas.core import algorithms, common as com, groupby, nanops, ops
+from pandas.core import algorithms, common as com, nanops, ops
 from pandas.core.accessor import CachedAccessor
 from pandas.core.arrays import Categorical, ExtensionArray
 from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin as DatetimeLikeArray
 from pandas.core.arrays.sparse import SparseFrameAccessor
 from pandas.core.generic import NDFrame, _shared_docs
+from pandas.core.groupby import generic as grp_generic
 from pandas.core.indexes import base as ibase
 from pandas.core.indexes.api import Index, ensure_index, ensure_index_from_sequences
 from pandas.core.indexes.datetimes import DatetimeIndex
@@ -5571,13 +5572,13 @@ def groupby(
         group_keys: bool = True,
         squeeze: bool = False,
         observed: bool = False,
-    ) -> "groupby.DataFrameGroupBy":
+    ) -> "grp_generic.DataFrameGroupBy":
 
         if level is None and by is None:
             raise TypeError("You have to supply one of 'by' and 'level'")
         axis = self._get_axis_number(axis)
 
-        return groupby.DataFrameGroupBy(
+        return grp_generic.DataFrameGroupBy(
             obj=self,
             keys=by,
             axis=axis,

pandas/core/reshape/merge.py

@@ -41,6 +41,7 @@
 
 from pandas import Categorical, Index, MultiIndex
 from pandas._typing import FrameOrSeries
+from pandas.core import groupby
 import pandas.core.algorithms as algos
 from pandas.core.arrays.categorical import _recode_for_categories
 import pandas.core.common as com
@@ -113,6 +114,7 @@ def _groupby_and_merge(
         by = [by]
 
     lby = left.groupby(by, sort=False)
+    rby = None  # type: Optional[groupby.DataFrameGroupBy]
 
     # if we can groupby the rhs
     # then we can get vastly better perf
@@ -132,7 +134,7 @@ def _groupby_and_merge(
                 right = _right
         rby = right.groupby(by, sort=False)
     except KeyError:
-        rby = None
+        pass
 
     for key, lhs in lby:
 

pandas/core/series.py

@@ -47,7 +47,7 @@
 )
 
 import pandas as pd
-from pandas.core import algorithms, base, generic, groupby, nanops, ops
+from pandas.core import algorithms, base, generic, nanops, ops
 from pandas.core.accessor import CachedAccessor
 from pandas.core.arrays import ExtensionArray, try_cast_to_ea
 from pandas.core.arrays.categorical import Categorical, CategoricalAccessor
@@ -59,6 +59,7 @@
     is_empty_data,
     sanitize_array,
 )
+from pandas.core.groupby import generic as grp_generic
 from pandas.core.indexers import maybe_convert_indices
 from pandas.core.indexes.accessors import CombinedDatetimelikeProperties
 from pandas.core.indexes.api import (
@@ -1630,13 +1631,13 @@ def groupby(
         group_keys: bool = True,
         squeeze: bool = False,
         observed: bool = False,
-    ) -> "groupby.SeriesGroupBy":
+    ) -> "grp_generic.SeriesGroupBy":
 
         if level is None and by is None:
             raise TypeError("You have to supply one of 'by' and 'level'")
         axis = self._get_axis_number(axis)
 
-        return groupby.SeriesGroupBy(
+        return grp_generic.SeriesGroupBy(
             obj=self,
             keys=by,
             axis=axis,