GroupBy[Series].count() return type should be Series[int] (#966)

* GroupBy[Series].count() return type should be Series[int]

* Use np.integer instead of np.int_

* Update pyright requirement '>=1.1.369' -> '>=1.1.374'

Author: chrisyeh96

pandas-stubs/core/groupby/groupby.pyi

@@ -176,7 +176,10 @@ class GroupBy(BaseGroupBy[NDFrameT]):
     @overload
     def all(self: GroupBy[DataFrame], skipna: bool = ...) -> DataFrame: ...
     @final
-    def count(self) -> NDFrameT: ...
+    @overload
+    def count(self: GroupBy[Series]) -> Series[int]: ...
+    @overload
+    def count(self: GroupBy[DataFrame]) -> DataFrame: ...
     @final
     def mean(
         self,

pyproject.toml

@@ -40,7 +40,7 @@ mypy = "1.10.1"
 pandas = "2.2.2"
 pyarrow = ">=10.0.1"
 pytest = ">=7.1.2"
-pyright = ">=1.1.369"
+pyright = ">= 1.1.374"
 poethepoet = ">=0.16.5"
 loguru = ">=0.6.0"
 typing-extensions = ">=4.4.0"

tests/test_frame.py

@@ -1025,6 +1025,7 @@ def test_types_groupby_methods() -> None:
     check(assert_type(df.groupby("col1").sum(), pd.DataFrame), pd.DataFrame)
     check(assert_type(df.groupby("col1").prod(), pd.DataFrame), pd.DataFrame)
     check(assert_type(df.groupby("col1").sample(), pd.DataFrame), pd.DataFrame)
+    check(assert_type(df.groupby("col1").count(), pd.DataFrame), pd.DataFrame)
     check(
         assert_type(df.groupby("col1").value_counts(normalize=False), "pd.Series[int]"),
         pd.Series,

tests/test_series.py

@@ -676,6 +676,13 @@ def test_types_groupby_methods() -> None:
     check(assert_type(s.groupby(level=0).idxmax(), pd.Series), pd.Series)
     check(assert_type(s.groupby(level=0).idxmin(), pd.Series), pd.Series)
 
+    s2 = pd.Series(["w", "x", "y", "z"], index=[3, 4, 3, 4], dtype=str)
+    check(
+        assert_type(s2.groupby(level=0).count(), "pd.Series[int]"),
+        pd.Series,
+        np.integer,
+    )
+
 
 def test_groupby_result() -> None:
     # GH 142