Fix tests and add documentation

Author: maushumee

doc/source/whatsnew/v3.0.0.rst

@@ -610,6 +610,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrameGroupBy.agg` that raises ``AttributeError`` when there is dictionary input and duplicated columns, instead of returning a DataFrame with the aggregation of all duplicate columns. (:issue:`55041`)
 - Bug in :meth:`DataFrameGroupBy.apply` that was returning a completely empty DataFrame when all return values of ``func`` were ``None`` instead of returning an empty DataFrame with the original columns and dtypes. (:issue:`57775`)
 - Bug in :meth:`DataFrameGroupBy.apply` with ``as_index=False`` that was returning :class:`MultiIndex` instead of returning :class:`Index`. (:issue:`58291`)
+- Bug in :meth:`DataFrameGroupBy.cumsum` and :meth:`DataFrameGroupBy.cumprod` where ``numeric_only`` parameter was passed indirectly through kwargs instead of passing directly. (:issue:`58811`)
 - Bug in :meth:`DataFrameGroupBy.cumsum` where it did not return the correct dtype when the label contained ``None``. (:issue:`58811`)
 - Bug in :meth:`DataFrameGroupby.transform` and :meth:`SeriesGroupby.transform` with a reducer and ``observed=False`` that coerces dtype to float when there are unobserved categories. (:issue:`55326`)
 - Bug in :meth:`Rolling.apply` where the applied function could be called on fewer than ``min_period`` periods if ``method="table"``. (:issue:`58868`)

pandas/tests/groupby/test_api.py

@@ -185,7 +185,7 @@ def test_frame_consistency(groupby_func):
     elif groupby_func in ("cummax", "cummin"):
         exclude_expected = {"axis", "skipna", "args"}
     elif groupby_func in ("cumprod", "cumsum"):
-        exclude_expected = {"axis", "skipna", "numeric_only"}
+        exclude_expected = {"axis", "skipna"}
     elif groupby_func in ("pct_change",):
         exclude_expected = {"kwargs"}
     elif groupby_func in ("rank",):
@@ -245,6 +245,7 @@ def test_series_consistency(request, groupby_func):
         exclude_result = {"numeric_only"}
     elif groupby_func in ("cumprod", "cumsum"):
         exclude_expected = {"skipna"}
+        exclude_result = {"numeric_only"}
     elif groupby_func in ("pct_change",):
         exclude_expected = {"kwargs"}
     elif groupby_func in ("rank",):