BUG: value_counts can handle the case even with empty groups (#28479)

doc/source/whatsnew/v1.0.0.rst

@@ -412,6 +412,7 @@ Other
 - :meth:`DataFrame.to_csv` and :meth:`Series.to_csv` now support dicts as ``compression`` argument with key ``'method'`` being the compression method and others as additional compression options when the compression method is ``'zip'``. (:issue:`26023`)
 - Bug in :meth:`Series.diff` where a boolean series would incorrectly raise a ``TypeError`` (:issue:`17294`)
 - :meth:`Series.append` will no longer raise a ``TypeError`` when passed a tuple of ``Series`` (:issue:`28410`)
+- :meth:`SeriesGroupBy.value_counts` will be able to handle the case even when the :class:`Grouper` makes empty groups (:issue: 28479)
 - Fix corrupted error message when calling ``pandas.libs._json.encode()`` on a 0d array (:issue:`18878`)
 - Fix :class:`AbstractHolidayCalendar` to return correct results for
   years after 2030 (now goes up to 2200) (:issue:`27790`)

pandas/core/sorting.py

@@ -162,6 +162,10 @@ def decons_obs_group_ids(comp_ids, obs_ids, shape, labels, xnull):
     xnull: boolean,
         if nulls are excluded; i.e. -1 labels are passed through
     """
+    labels = list(labels)
+    unique_comp_ids = np.unique(comp_ids)
+    if (shape[0] != len(unique_comp_ids)) and (shape[0] == len(labels[0])):
+        return [unique_comp_ids]
 
     if not xnull:
         lift = np.fromiter(((a == -1).any() for a in labels), dtype="i8")

pandas/tests/groupby/test_value_counts.py

@@ -4,12 +4,12 @@
 and proper parameter handling
 """
 
-from itertools import product
+from itertools import cycle, islice, product
 
 import numpy as np
 import pytest
 
-from pandas import DataFrame, MultiIndex, Series, date_range
+from pandas import DataFrame, Grouper, MultiIndex, Series, date_range
 from pandas.util import testing as tm
 
 
@@ -79,3 +79,25 @@ def rebuild_index(df):
     # have to sort on index because of unstable sort on values
     left, right = map(rebuild_index, (left, right))  # xref GH9212
     tm.assert_series_equal(left.sort_index(), right.sort_index())
+
+
+@pytest.mark.parametrize("freq", ["1D", "2D", "1W", "1Y"])
+@pytest.mark.parametrize("size", [100, 1000])
+@pytest.mark.parametrize("frac", [0.1, 0.5, 1])
+def test_series_groupby_value_counts_with_grouper(freq, size, frac):
+    # GH28479
+    df = DataFrame.from_dict(
+        {
+            "date": date_range("2019-09-25", periods=size),
+            "name": islice(cycle("abc"), size),
+        }
+    ).sample(frac=frac)
+
+    gr = df.groupby(Grouper(key="date", freq=freq))["name"]
+
+    # have to sort on index because of unstable sort on values xref GH9212
+    result = gr.value_counts().sort_index()
+    expected = gr.apply(Series.value_counts).sort_index()
+    expected.index.names = result.index.names
+
+    tm.assert_series_equal(result, expected)