Fixed warnings

Author: rsm-23

pandas/core/frame.py

@@ -11129,11 +11129,27 @@ 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,
+        numeric_only: bool = False,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
+        self._get_numeric_data() if numeric_only else self
         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,
+        numeric_only: bool = False,
+        skipna: bool = True,
+        *args,
+        **kwargs,
+    ):
+        self._get_numeric_data() if numeric_only else self
         return NDFrame.cumprod(self, axis, skipna, *args, **kwargs)
 
     def nunique(self, axis: Axis = 0, dropna: bool = True) -> Series:

pandas/core/generic.py

@@ -11578,6 +11578,7 @@ def _accum_func(
         *args,
         **kwargs,
     ):
+        skipna = nv.validate_cum_func_with_skipna(skipna, args, kwargs, name)
         if name not in ["cumprod", "cumsum"]:
             skipna = nv.validate_cum_func_with_skipna(skipna, args, kwargs, name)
         if axis is None:

pandas/tests/groupby/test_api.py

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

pandas/tests/groupby/test_function.py

@@ -565,8 +565,9 @@ 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'"
-        with pytest.raises(TypeError, match=msg):
-            method(*args, **kwargs)
+        if groupby_func in ["cumprod", "cumsum"]:
+            with tm.assert_produces_warning(FutureWarning, match=warn_msg):
+                method(*args, **kwargs)
     elif groupby_func not in has_axis:
         msg = "got an unexpected keyword argument 'axis'"
         with pytest.raises(TypeError, match=msg):

pandas/tests/series/test_api.py

@@ -231,9 +231,9 @@ def test_series_datetimelike_attribute_access_invalid(self):
             ("cummax", False),
             ("shift", False),
             ("diff", False),
-            ("cumsum", True),
+            ("cumsum", False),
             ("cummin", False),
-            ("cumprod", True),
+            ("cumprod", False),
             ("fillna", False),
             ("ffill", False),
             ("pad", False),
@@ -276,7 +276,7 @@ def test_numeric_only(self, kernel, has_numeric_only, dtype):
             )
             with pytest.raises(TypeError, match=msg):
                 method(*args, numeric_only=True)
-        elif dtype is object and kernel not in ["cumprod", "cumsum"]:
+        elif dtype is object:
             msg = f"Series.{kernel} does not allow numeric_only=True with non-numeric"
             with pytest.raises(TypeError, match=msg):
                 method(*args, numeric_only=True)