Fixed warnings and modified tests

Author: rsm-23

pandas/core/frame.py

@@ -11129,11 +11129,23 @@ def cummax(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs)
         return NDFrame.cummax(self, axis, skipna, *args, **kwargs)
 
     @doc(make_doc("cumsum", ndim=2))
-    def cumsum(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs):
+    def cumsum(
+        self,
+        axis: Axis | None = None,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
         return NDFrame.cumsum(self, axis, skipna, *args, **kwargs)
 
     @doc(make_doc("cumprod", 2))
-    def cumprod(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs):
+    def cumprod(
+        self,
+        axis: Axis | None = None,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
         return NDFrame.cumprod(self, axis, skipna, *args, **kwargs)
 
     def nunique(self, axis: Axis = 0, dropna: bool = True) -> Series:

pandas/core/generic.py

@@ -11578,7 +11578,6 @@ def _accum_func(
         *args,
         **kwargs,
     ):
-        skipna = nv.validate_cum_func_with_skipna(skipna, args, kwargs, name)
         if axis is None:
             axis = 0
         else:

pandas/core/groupby/groupby.py

@@ -4573,6 +4573,7 @@ def cumprod(
         axis: Axis | lib.NoDefault = lib.no_default,
         numeric_only: bool = False,
         skipna: bool = True,
+        **kwargs,
     ) -> NDFrameT:
         """
         Cumulative product for each group.
@@ -4633,11 +4634,13 @@ def cumprod(
             axis = 0
 
         if axis != 0:
-            f = lambda x: x.cumprod(axis=axis, numeric_only=numeric_only, skipna=skipna)
+            f = lambda x: x.cumprod(
+                axis=axis, numeric_only=numeric_only, skipna=skipna, **kwargs
+            )
             return self._python_apply_general(f, self._selected_obj, is_transform=True)
 
         return self._cython_transform(
-            "cumprod", numeric_only=numeric_only, skipna=skipna
+            "cumprod", numeric_only=numeric_only, skipna=skipna, **kwargs
         )
 
     @final
@@ -4648,6 +4651,7 @@ def cumsum(
         axis: Axis | lib.NoDefault = lib.no_default,
         numeric_only: bool = False,
         skipna: bool = True,
+        **kwargs,
     ) -> NDFrameT:
         """
         Cumulative sum for each group.
@@ -4708,11 +4712,13 @@ def cumsum(
             axis = 0
 
         if axis != 0:
-            f = lambda x: x.cumsum(axis=axis, numeric_only=numeric_only, skipna=skipna)
+            f = lambda x: x.cumsum(
+                axis=axis, numeric_only=numeric_only, skipna=skipna, **kwargs
+            )
             return self._python_apply_general(f, self._selected_obj, is_transform=True)
 
         return self._cython_transform(
-            "cumsum", numeric_only=numeric_only, skipna=skipna
+            "cumsum", numeric_only=numeric_only, skipna=skipna, **kwargs
         )
 
     @final

pandas/core/series.py

@@ -6204,9 +6204,23 @@ def cummax(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs)
         return NDFrame.cummax(self, axis, skipna, *args, **kwargs)
 
     @doc(make_doc("cumsum", ndim=1))
-    def cumsum(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs):
-        return NDFrame.cumsum(self, axis, skipna, *args, **kwargs)
+    def cumsum(
+        self,
+        axis: Axis | None = None,
+        numeric_only: bool = False,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
+        return NDFrame.cumsum(self, axis, numeric_only, skipna, *args, **kwargs)
 
     @doc(make_doc("cumprod", 1))
-    def cumprod(self, axis: Axis | None = None, skipna: bool = True, *args, **kwargs):
-        return NDFrame.cumprod(self, axis, skipna, *args, **kwargs)
+    def cumprod(
+        self,
+        axis: Axis | None = None,
+        numeric_only: bool = False,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
+        return NDFrame.cumprod(self, axis, numeric_only, skipna, *args, **kwargs)

pandas/tests/groupby/test_api.py

@@ -184,7 +184,8 @@ def test_frame_consistency(groupby_func):
         exclude_expected = {"skipna", "args"}
         exclude_result = {"numeric_only"}
     elif groupby_func in ("cumprod", "cumsum"):
-        exclude_expected = {"skipna"}
+        exclude_expected = {"args", "kwargs"}
+        exclude_result = {"numeric_only"}
     elif groupby_func in ("pct_change",):
         exclude_expected = {"kwargs"}
         exclude_result = {"axis"}
@@ -242,7 +243,7 @@ def test_series_consistency(request, groupby_func):
         exclude_expected = {"skipna", "args"}
         exclude_result = {"numeric_only"}
     elif groupby_func in ("cumprod", "cumsum"):
-        exclude_expected = {"skipna"}
+        exclude_expected = {"args", "kwargs"}
     elif groupby_func in ("pct_change",):
         exclude_expected = {"kwargs"}
         exclude_result = {"axis"}

pandas/tests/groupby/test_function.py

@@ -547,7 +547,7 @@ def test_axis1_numeric_only(request, groupby_func, numeric_only):
         kwargs["numeric_only"] = numeric_only
 
     # Functions without numeric_only and axis args
-    no_args = ("cumprod", "cumsum", "diff", "fillna", "pct_change", "rank", "shift")
+    no_args = ("diff", "fillna", "pct_change", "rank", "shift")
     # Functions with axis args
     has_axis = (
         "cumprod",
@@ -565,13 +565,8 @@ def test_axis1_numeric_only(request, groupby_func, numeric_only):
     warn_msg = f"DataFrameGroupBy.{groupby_func} with axis=1 is deprecated"
     if numeric_only is not None and groupby_func in no_args:
         msg = "got an unexpected keyword argument 'numeric_only'"
-        if groupby_func in ["cumprod", "cumsum"]:
-            with pytest.raises(TypeError, match=msg):
-                with tm.assert_produces_warning(FutureWarning, match=warn_msg):
-                    method(*args, **kwargs)
-        else:
-            with pytest.raises(TypeError, match=msg):
-                method(*args, **kwargs)
+        with pytest.raises(TypeError, match=msg):
+            method(*args, **kwargs)
     elif groupby_func not in has_axis:
         msg = "got an unexpected keyword argument 'axis'"
         with pytest.raises(TypeError, match=msg):
@@ -814,11 +809,13 @@ def test_numpy_compat(func):
     g = df.groupby("A")
 
     msg = "numpy operations are not valid with groupby"
+    warn_msg = f"DataFrameGroupBy.{func} with axis=1 is deprecated"
 
-    with pytest.raises(UnsupportedFunctionCall, match=msg):
-        getattr(g, func)(1, 2, 3)
-    with pytest.raises(UnsupportedFunctionCall, match=msg):
-        getattr(g, func)(foo=1)
+    with pytest.raises(FutureWarning, match=warn_msg):
+        with pytest.raises(UnsupportedFunctionCall, match=msg):
+            getattr(g, func)(1, 2, 3)
+        with pytest.raises(UnsupportedFunctionCall, match=msg):
+            getattr(g, func)(foo=1)
 
 
 def test_cummin(dtypes_for_minmax):