add whatsnew entry (#42618)

Author: neelmraman

doc/source/whatsnew/v1.3.1.rst

@@ -25,6 +25,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.isin` and :meth:`Series.isin` raising ``TypeError`` with nullable data containing at least one missing value (:issue:`42405`)
 - Regression in :func:`concat` between objects with bool dtype and integer dtype casting to object instead of to integer (:issue:`42092`)
 - Bug in :class:`Series` constructor not accepting a ``dask.Array`` (:issue:`38645`)
+- Fixed regression in :meth:`SeriesGroupBy.value_counts` that resulted in an ``IndexError`` when called on a Series with one row (:issue:`42618`)
 
 .. ---------------------------------------------------------------------------
 

pandas/tests/groupby/test_value_counts.py

@@ -122,44 +122,29 @@ def test_series_groupby_value_counts_with_grouper():
     tm.assert_series_equal(result, expected)
 
 
-def test_series_groupby_value_counts_empty():
+@pytest.mark.parametrize("columns", [["A", "B"], ["A", "B", "C"]])
+def test_series_groupby_value_counts_empty(columns):
     # GH39172
-    df = DataFrame(columns=["A", "B"])
-    dfg = df.groupby("A")
+    df = DataFrame(columns=columns)
+    dfg = df.groupby(columns[:-1])
 
-    result = dfg["B"].value_counts()
-    expected = Series([], name="B", dtype=result.dtype)
-    expected.index = MultiIndex.from_arrays([[]] * 2, names=["A", "B"])
+    result = dfg[columns[-1]].value_counts()
+    expected = Series([], name=columns[-1], dtype=result.dtype)
+    expected.index = MultiIndex.from_arrays([[]] * len(columns), names=columns)
 
     tm.assert_series_equal(result, expected)
 
-    df = DataFrame(columns=["A", "B", "C"])
-    dfg = df.groupby(["A", "B"])
 
-    result = dfg["C"].value_counts()
-    expected = Series([], name="C", dtype=result.dtype)
-    expected.index = MultiIndex.from_arrays([[]] * 3, names=["A", "B", "C"])
-
-    tm.assert_series_equal(result, expected)
-
-
-def test_series_groupby_value_counts_one_row():
+@pytest.mark.parametrize("columns", [["A", "B"], ["A", "B", "C"]])
+def test_series_groupby_value_counts_one_row(columns):
     # GH42618
-    df = DataFrame([[1, 2]], columns=["A", "B"])
-    dfg = df.groupby("A")
+    df = DataFrame(data=[range(len(columns))], columns=columns)
+    dfg = df.groupby(columns[:-1])
 
-    result = dfg["B"].value_counts()
-    expected = df.value_counts()
+    result = dfg[columns[-1]].value_counts()
+    expected = df.value_counts().rename(columns[-1])
 
-    tm.assert_series_equal(result, expected, check_names=False)
-
-    df = DataFrame([[1, 2, 3]], columns=["A", "B", "C"])
-    dfg = df.groupby(["A", "B"])
-
-    result = dfg["C"].value_counts()
-    expected = df.value_counts()
-
-    tm.assert_series_equal(result, expected, check_names=False)
+    tm.assert_series_equal(result, expected)
 
 
 def test_series_groupby_value_counts_on_categorical():