BUG: Mitigate division with zero in roll_var (pandas-dev#42459)

Author: benHeid

doc/source/whatsnew/v1.4.0.rst

@@ -261,7 +261,7 @@ Groupby/resample/rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 - Fixed bug in :meth:`SeriesGroupBy.apply` where passing an unrecognized string argument failed to raise ``TypeError`` when the underlying ``Series`` is empty (:issue:`42021`)
 - Bug in :meth:`Series.rolling.apply`, :meth:`DataFrame.rolling.apply`, :meth:`Series.expanding.apply` and :meth:`DataFrame.expanding.apply` with ``engine="numba"`` where ``*args`` were being cached with the user passed function (:issue:`42287`)
--
+- Bug in :meth:`DataFrame.groupby.rolling.var` would calculate the rolling variance only on the first group (:issue:`42442`)
 
 Reshaping
 ^^^^^^^^^

pandas/_libs/window/aggregations.pyx

@@ -310,7 +310,10 @@ cdef inline void add_var(float64_t val, float64_t *nobs, float64_t *mean_x,
     t = y - mean_x[0]
     compensation[0] = t + mean_x[0] - y
     delta = t
-    mean_x[0] = mean_x[0] + delta / nobs[0]
+    if nobs[0]:
+        mean_x[0] = mean_x[0] + delta / nobs[0]
+    else:
+        mean_x[0] = 0
     ssqdm_x[0] = ssqdm_x[0] + (val - prev_mean) * (val - mean_x[0])
 
 

pandas/tests/window/test_groupby.py

@@ -695,6 +695,31 @@ def test_groupby_rolling_object_doesnt_affect_groupby_apply(self):
         assert not g.mutated
         assert not g.grouper.mutated
 
+    @pytest.mark.parametrize(
+        ("window", "min_periods", "closed", "expected"),
+        [
+            (2, 0, "left", [None, 0.0, 1.0, 1.0, None, 0.0, 1.0, 1.0]),
+            (2, 2, "left", [None, None, 1.0, 1.0, None, None, 1.0, 1.0]),
+            (4, 4, "left", [None, None, None, None, None, None, None, None]),
+            (4, 4, "right", [None, None, None, 5.0, None, None, None, 5.0]),
+        ],
+    )
+    def test_groupby_rolling_var(self, window, min_periods, closed, expected):
+        df = DataFrame([1, 2, 3, 4, 5, 6, 7, 8])
+        result = (
+            df.groupby([1, 2, 1, 2, 1, 2, 1, 2])
+            .rolling(window=window, min_periods=min_periods, closed=closed)
+            .var(0)
+        )
+        expected_result = DataFrame(
+            np.array(expected, dtype="float64"),
+            index=MultiIndex(
+                levels=[[1, 2], [0, 1, 2, 3, 4, 5, 6, 7]],
+                codes=[[0, 0, 0, 0, 1, 1, 1, 1], [0, 2, 4, 6, 1, 3, 5, 7]],
+            ),
+        )
+        tm.assert_frame_equal(result, expected_result)
+
     @pytest.mark.parametrize(
         "columns", [MultiIndex.from_tuples([("A", ""), ("B", "C")]), ["A", "B"]]
     )