DOC/TYP: Fixed typing and doc

pandas/core/aggregation.py

@@ -5,13 +5,18 @@
 
 from collections import defaultdict
 from functools import partial
-from typing import Any, DefaultDict, List, Sequence, Tuple
+from typing import TYPE_CHECKING, Any, DefaultDict, Dict, List, Sequence, Tuple
+
+from pandas._typing import Scalar
 
 from pandas.core.dtypes.common import is_dict_like, is_list_like
 
 import pandas.core.common as com
 from pandas.core.indexes.api import Index
 
+if TYPE_CHECKING:
+    import numpy as np  # noqa: F401
+
 
 def is_multi_agg_with_relabel(**kwargs) -> bool:
     """
@@ -39,7 +44,9 @@ def is_multi_agg_with_relabel(**kwargs) -> bool:
     )
 
 
-def normalize_keyword_aggregation(kwargs: dict) -> Tuple[dict, List[str], List[int]]:
+def normalize_keyword_aggregation(
+    kwargs: Dict[str, str]
+) -> Tuple[DefaultDict[str, List[Scalar]], Tuple[str, ...], "np.ndarray"]:
     """
     Normalize user-provided "named aggregation" kwargs.
     Transforms from the new ``Mapping[str, NamedAgg]`` style kwargs
@@ -51,11 +58,11 @@ def normalize_keyword_aggregation(kwargs: dict) -> Tuple[dict, List[str], List[i
 
     Returns
     -------
-    aggspec : dict
+    aggspec : collections.defaultdict of lists
         The transformed kwargs.
-    columns : List[str]
+    columns : tuple
         The user-provided keys.
-    col_idx_order : List[int]
+    col_idx_order :  numpy.ndarray
         List of columns indices.
 
     Examples

pandas/core/groupby/generic.py

@@ -14,11 +14,13 @@
     TYPE_CHECKING,
     Any,
     Callable,
+    DefaultDict,
     Dict,
     FrozenSet,
     Iterable,
     List,
     Mapping,
+    Optional,
     Sequence,
     Tuple,
     Type,
@@ -30,7 +32,7 @@
 import numpy as np
 
 from pandas._libs import Timestamp, lib
-from pandas._typing import FrameOrSeries
+from pandas._typing import FrameOrSeries, Scalar
 from pandas.util._decorators import Appender, Substitution, doc
 
 from pandas.core.dtypes.cast import (
@@ -909,7 +911,9 @@ class DataFrameGroupBy(GroupBy[DataFrame]):
         axis="",
     )
     @Appender(_shared_docs["aggregate"])
-    def aggregate(self, func=None, *args, **kwargs):
+    def aggregate(
+        self, func: Optional[DefaultDict[str, List[Scalar]]] = None, *args, **kwargs
+    ):
 
         relabeling = func is None and is_multi_agg_with_relabel(**kwargs)
         if relabeling: