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

    * If applying rep to recons_labels go fail, use ids which has no
      consecutive duplicates instead.

Author: dongho-jung

doc/source/whatsnew/v1.0.0.rst

@@ -299,6 +299,7 @@ Other
 - Using :meth:`DataFrame.replace` with overlapping keys in a nested dictionary will no longer raise, now matching the behavior of a flat dictionary (:issue:`27660`)
 - :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`)
 - :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)
 
 .. _whatsnew_1000.contributors:
 

pandas/core/groupby/generic.py

@@ -1259,7 +1259,14 @@ def value_counts(
         rep = partial(np.repeat, repeats=np.add.reduceat(inc, idx))
 
         # multi-index components
-        labels = list(map(rep, self.grouper.recons_labels)) + [llab(lab, inc)]
+        try:
+            labels = list(map(rep, self.grouper.recons_labels)) + [llab(lab, inc)]
+        except ValueError:
+            # If applying rep to recons_labels go fail, use ids which has no
+            # consecutive duplicates instead.
+            _ids_idx = np.ones(len(ids), dtype=bool)
+            _ids_idx[1:] = ids[1:] != ids[:-1]
+            labels = list(map(rep, [ids[_ids_idx]])) + [llab(lab, inc)]
         levels = [ping.group_index for ping in self.grouper.groupings] + [lev]
         names = self.grouper.names + [self._selection_name]
 

pandas/tests/groupby/test_value_counts.py

@@ -9,7 +9,7 @@
 import numpy as np
 import pytest
 
-from pandas import DataFrame, MultiIndex, Series, date_range
+from pandas import DataFrame, MultiIndex, Series, date_range, Grouper
 from pandas.util import testing as tm
 
 
@@ -79,3 +79,28 @@ 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, size, frac", product(["1D", "2D", "1W", "1Y"], [100, 1000], [0.1, 0.5, 1])
+)
+def test_series_groupby_value_counts_with_grouper(freq, size, frac):
+    np.random.seed(42)
+
+    df = DataFrame.from_dict(
+        {
+            "date": date_range("2019-09-25", periods=size),
+            "name": np.random.choice(list("abcd"), 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
+    )  # .apply(Series.value_counts) can't create all names
+
+    tm.assert_series_equal(result, expected)