pandas\core\groupby\grouper.py:422: error: Implicit generic "Any". Use "typing.Dict" and specify generic parameters

Author: simonjayhawkins

pandas/core/arrays/categorical.py

@@ -1,6 +1,6 @@
 import operator
 from shutil import get_terminal_size
-from typing import List, Type, Union, cast
+from typing import Dict, Hashable, List, Type, Union, cast
 from warnings import warn
 
 import numpy as np
@@ -2067,7 +2067,7 @@ def __setitem__(self, key, value):
         lindexer = self._maybe_coerce_indexer(lindexer)
         self._codes[key] = lindexer
 
-    def _reverse_indexer(self):
+    def _reverse_indexer(self) -> Dict[Hashable, np.ndarray]:
         """
         Compute the inverse of a categorical, returning
         a dict of categories -> indexers.
@@ -2097,8 +2097,8 @@ def _reverse_indexer(self):
             self.codes.astype("int64"), categories.size
         )
         counts = counts.cumsum()
-        result = (r[start:end] for start, end in zip(counts, counts[1:]))
-        result = dict(zip(categories, result))
+        _result = (r[start:end] for start, end in zip(counts, counts[1:]))
+        result = dict(zip(categories, _result))
         return result
 
     # reduction ops #

pandas/core/groupby/grouper.py

@@ -3,7 +3,7 @@
 split-apply-combine paradigm.
 """
 
-from typing import Hashable, List, Optional, Tuple
+from typing import Dict, Hashable, List, Optional, Tuple
 
 import numpy as np
 
@@ -419,7 +419,7 @@ def _make_codes(self) -> None:
             self._group_index = uniques
 
     @cache_readonly
-    def groups(self) -> dict:
+    def groups(self) -> Dict[Hashable, np.ndarray]:
         return self.index.groupby(Categorical.from_codes(self.codes, self.group_index))
 
 

pandas/core/indexes/base.py

@@ -1,7 +1,7 @@
 from datetime import datetime
 import operator
 from textwrap import dedent
-from typing import FrozenSet, Hashable, Optional, Union
+from typing import Dict, FrozenSet, Hashable, Optional, Union
 import warnings
 
 import numpy as np
@@ -4594,7 +4594,7 @@ def _maybe_promote(self, other):
                 return self.astype("object"), other.astype("object")
         return self, other
 
-    def groupby(self, values):
+    def groupby(self, values) -> Dict[Hashable, np.ndarray]:
         """
         Group the index labels by a given array of values.
 
@@ -4605,7 +4605,7 @@ def groupby(self, values):
 
         Returns
         -------
-        groups : dict
+        dict
             {group name -> group labels}
         """