BUG: resample by BusinessHour raises ValueError

closes #12351

Author: Younggun Kim

doc/source/whatsnew/v0.21.0.txt

@@ -102,6 +102,7 @@ Plotting
 Groupby/Resample/Rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
+- Bug in ``.resample(..)`` with a ``BusinessHour`` raises ``ValueError`` (:issue:`12351`)
 
 
 Sparse

pandas/core/resample.py

@@ -13,7 +13,8 @@
 from pandas.tseries.frequencies import to_offset, is_subperiod, is_superperiod
 from pandas.core.indexes.datetimes import DatetimeIndex, date_range
 from pandas.core.indexes.timedeltas import TimedeltaIndex
-from pandas.tseries.offsets import DateOffset, Tick, Day, _delta_to_nanoseconds
+from pandas.tseries.offsets import (DateOffset, Tick, Day, _delta_to_nanoseconds,
+                                    BusinessHourMixin)
 from pandas.core.indexes.period import PeriodIndex, period_range
 import pandas.core.common as com
 import pandas.core.algorithms as algos
@@ -1271,8 +1272,11 @@ def _get_range_edges(first, last, offset, closed='left', base=0):
         if (is_day and day_nanos % offset.nanos == 0) or not is_day:
             return _adjust_dates_anchored(first, last, offset,
                                           closed=closed, base=base)
-
-    if not isinstance(offset, Tick):  # and first.time() != last.time():
+    # GH12351
+    elif issubclass(type(offset), BusinessHourMixin):
+        first = offset.rollback(first)
+        last = offset.rollforward(last + offset)
+    else:
         # hack!
         first = first.normalize()
         last = last.normalize()

pandas/tests/test_resample.py

@@ -2564,6 +2564,22 @@ def test_upsample_daily_business_daily(self):
         expected = ts.asfreq('H', how='s').reindex(exp_rng)
         assert_series_equal(result, expected)
 
+
+    # GH12351
+    def test_resample_business_hourly(self):
+        rng = pd.date_range(start='2017-05-18 00:00:00',
+                            end='2017-05-19 23:00:00',
+                            freq='H')
+        expected_rng = pd.date_range(start='2017-05-18 00:00:00',
+                                    end='2017-05-19 23:00:00',
+                                    freq='BH')
+        ts = Series(1, index=rng)
+        result = ts.asfreq('BH')
+        expected_ts = Series(1, index=expected_rng)
+
+        assert_series_equal(result, expected_ts)
+
+
     def test_resample_irregular_sparse(self):
         dr = date_range(start='1/1/2012', freq='5min', periods=1000)
         s = Series(np.array(100), index=dr)