removed redundant comment, added issue number, updated doc

Author: Petroncini

doc/source/whatsnew/v3.0.0.rst

@@ -652,6 +652,7 @@ Plotting
 Groupby/resample/rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 - Bug in :meth:`.DataFrameGroupBy.__len__` and :meth:`.SeriesGroupBy.__len__` would raise when the grouping contained NA values and ``dropna=False`` (:issue:`58644`)
+- Bug in :meth:`.DataFrameGroupBy.any` that returned True for groups where all Timedelta values are NaT. (:issue:`59782`)
 - Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby argument ``dropna`` (:issue:`55919`)
 - Bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
 - Bug in :meth:`.DataFrameGroupBy.quantile` when ``interpolation="nearest"`` is inconsistent with :meth:`DataFrame.quantile` (:issue:`47942`)

pandas/tests/groupby/test_grouping.py

@@ -1183,15 +1183,12 @@ def test_grouping_by_key_is_in_axis():
 
 
 def test_groupby_any_with_timedelta():
-    # Create a DataFrame with a single column containing a Timedelta and NaT
+    # GH#59712
     df = DataFrame({"value": [pd.Timedelta(1), pd.NaT]})
 
-    # Perform groupby().any() operation
     result = df.groupby(np.array([0, 1], dtype=np.int64))["value"].any()
 
-    # Expected result: group with NaT should return False
     expected = Series({0: True, 1: False}, name="value", dtype=bool)
     expected.index = expected.index.astype(np.int64)
 
-    # Check if the result matches the expected output
     tm.assert_series_equal(result, expected)