BUG: Resampling to "B" frequency with closed="right" and label="right" adds empty bins

doc/source/whatsnew/v3.0.0.rst

@@ -653,6 +653,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrameGroupby.transform` and :meth:`SeriesGroupby.transform` with a reducer and ``observed=False`` that coerces dtype to float when there are unobserved categories. (:issue:`55326`)
 - Bug in :meth:`Rolling.apply` where the applied function could be called on fewer than ``min_period`` periods if ``method="table"``. (:issue:`58868`)
 - Bug in :meth:`Series.resample` could raise when the the date range ended shortly before a non-existent time. (:issue:`58380`)
+- Bug in :meth:`Series.resample` where bin edges were not correct with closed="right" and label="right" for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`59495`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/resample.py

@@ -2173,7 +2173,11 @@ def _get_time_bins(self, ax: DatetimeIndex):
         if self.closed == "right":
             labels = binner
             if self.label == "right":
-                labels = labels[1:]
+                if binner.freqstr == "B":
+                    labels = labels[1:-1]
+                    bins = bins[0:-1]
+                else:
+                    labels = labels[1:]
         elif self.label == "right":
             labels = labels[1:]
 

pandas/tests/resample/test_datetime_index.py

@@ -637,7 +637,7 @@ def test_resample_reresample(unit):
     s = Series(np.random.default_rng(2).random(len(dti)), dti)
     bs = s.resample("B", closed="right", label="right").mean()
     result = bs.resample("8h").mean()
-    assert len(result) == 25
+    assert len(result) == 22
     assert isinstance(result.index.freq, offsets.DateOffset)
     assert result.index.freq == offsets.Hour(8)
 
@@ -2121,21 +2121,20 @@ def test_resample_c_b_closed_right(freq: str, unit):
 
 def test_resample_b_55282(unit):
     # https://github.com/pandas-dev/pandas/issues/55282
-    dti = date_range("2023-09-26", periods=6, freq="12h", unit=unit)
-    ser = Series([1, 2, 3, 4, 5, 6], index=dti)
+    dti = date_range("2023-09-26", periods=5, freq="12h", unit=unit)
+    ser = Series([1, 2, 3, 4, 5], index=dti)
     result = ser.resample("B", closed="right", label="right").mean()
 
     exp_dti = DatetimeIndex(
         [
             datetime(2023, 9, 26),
             datetime(2023, 9, 27),
             datetime(2023, 9, 28),
-            datetime(2023, 9, 29),
         ],
         freq="B",
     ).as_unit(unit)
     expected = Series(
-        [1.0, 2.5, 4.5, 6.0],
+        [1.0, 2.5, 4.5],
         index=exp_dti,
     )
     tm.assert_series_equal(result, expected)
@@ -2172,3 +2171,25 @@ def test_resample_A_raises(freq):
     s = Series(range(10), index=date_range("20130101", freq="D", periods=10))
     with pytest.raises(ValueError, match=msg):
         s.resample(freq).mean()
+
+
+def test_resample_b_59495():
+    # GH#59495
+    dti = date_range("8Aug2024", "13Aug2024", freq="D")
+    ser = Series(range(len(dti)), dti) + 1
+    result = ser.resample("B", closed="right", label="right").sum()
+
+    exp_dti = DatetimeIndex(
+        [
+            datetime(2024, 8, 8),
+            datetime(2024, 8, 9),
+            datetime(2024, 8, 12),
+            datetime(2024, 8, 13),
+        ],
+        freq="B",
+    ).as_unit("ns")
+    expected = Series(
+        [1, 2, 12, 6],
+        index=exp_dti,
+    )
+    tm.assert_series_equal(result, expected)