GH203 Split groupby with as_index

Author: loicdiridollou

pandas-stubs/core/frame.pyi

@@ -25,7 +25,10 @@ from pandas import (
 )
 from pandas.core.arraylike import OpsMixin
 from pandas.core.generic import NDFrame
-from pandas.core.groupby.generic import DataFrameGroupBy
+from pandas.core.groupby.generic import (
+    DataFrameGroupBy,
+    SeriesGroupBy,
+)
 from pandas.core.groupby.grouper import Grouper
 from pandas.core.indexers import BaseIndexer
 from pandas.core.indexes.base import Index
@@ -1052,18 +1055,30 @@ class DataFrame(NDFrame, OpsMixin):
         errors: IgnoreRaise = ...,
     ) -> None: ...
     @overload
-    def groupby(
+    def groupby(  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
         self,
         by: Scalar,
         axis: AxisIndex | NoDefault = ...,
         level: IndexLabel | None = ...,
-        as_index: _bool = ...,
+        as_index: Literal[False] = ...,
         sort: _bool = ...,
         group_keys: _bool = ...,
         observed: _bool | NoDefault = ...,
         dropna: _bool = ...,
     ) -> DataFrameGroupBy[Scalar]: ...
     @overload
+    def groupby(
+        self,
+        by: Scalar,
+        axis: AxisIndex | NoDefault = ...,
+        level: IndexLabel | None = ...,
+        as_index: Literal[True] = True,
+        sort: _bool = ...,
+        group_keys: _bool = ...,
+        observed: _bool | NoDefault = ...,
+        dropna: _bool = ...,
+    ) -> SeriesGroupBy: ...
+    @overload
     def groupby(
         self,
         by: DatetimeIndex,

pandas-stubs/core/groupby/groupby.pyi

@@ -236,7 +236,7 @@ class GroupBy(BaseGroupBy[NDFrameT]):
     @overload
     def size(self: GroupBy[Series]) -> Series[int]: ...
     @overload  # return type depends on `as_index` for dataframe groupby
-    def size(self: GroupBy[DataFrame]) -> DataFrame | Series[int]: ...
+    def size(self: GroupBy[DataFrame]) -> DataFrame: ...
     @final
     def sum(
         self,

tests/test_frame.py

@@ -1025,6 +1025,24 @@ def test_types_pivot_table() -> None:
     )
 
 
+def test_types_groupby_as_index() -> None:
+    df = pd.DataFrame({"a": [1, 2, 3]})
+    check(
+        assert_type(
+            df.groupby("a", as_index=False).size(),
+            pd.DataFrame,
+        ),
+        pd.DataFrame,
+    )
+    check(
+        assert_type(
+            df.groupby("a", as_index=True).size(),
+            "pd.Series[int]",
+        ),
+        pd.Series,
+    )
+
+
 def test_types_groupby() -> None:
     df = pd.DataFrame(data={"col1": [1, 1, 2], "col2": [3, 4, 5], "col3": [0, 1, 0]})
     df.index.name = "ind"
@@ -1048,7 +1066,7 @@ def test_types_groupby() -> None:
 
     df1: pd.DataFrame = df.groupby(by="col1").agg("sum")
     df2: pd.DataFrame = df.groupby(level="ind").aggregate("sum")
-    df3: pd.DataFrame = df.groupby(by="col1", sort=False, as_index=True).transform(
+    df3: pd.Series = df.groupby(by="col1", sort=False, as_index=True).transform(
         lambda x: x.max()
     )
     df4: pd.DataFrame = df.groupby(by=["col1", "col2"]).count()