BUG: resample by BusinessHour raises ValueError

closes pandas-dev#12351

Author: scari

doc/source/whatsnew/v0.18.2.txt

@@ -341,6 +341,7 @@ Bug Fixes
 - Bug in ``.resample(..)`` with a ``PeriodIndex`` not retaining its type or name with an empty ``DataFrame``appropriately when empty (:issue:`13212`)
 - Bug in ``groupby(..).resample(..)`` where passing some keywords would raise an exception (:issue:`13235`)
 - Bug in ``.tz_convert`` on a tz-aware ``DateTimeIndex`` that relied on index being sorted for correct results (:issue: `13306`)
+- Bug in ``.resample(..)`` with a ``BusinessHour`` raises ``ValueError`` (:issue:`12351`)
 
 
 

pandas/tseries/resample.py

@@ -12,7 +12,8 @@
 from pandas.tseries.frequencies import to_offset, is_subperiod, is_superperiod
 from pandas.tseries.index import DatetimeIndex, date_range
 from pandas.tseries.tdi import TimedeltaIndex
-from pandas.tseries.offsets import DateOffset, Tick, Day, _delta_to_nanoseconds
+from pandas.tseries.offsets import (DateOffset, Tick, Day, BusinessHour,
+                                    _delta_to_nanoseconds)
 from pandas.tseries.period import PeriodIndex, period_range
 import pandas.core.common as com
 import pandas.core.algorithms as algos
@@ -1213,8 +1214,13 @@ 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)
+    elif isinstance(offset, BusinessHour):
+        # GH12351 - normalize BH freq leads ValueError
+        first = Timestamp(offset.rollback(first))
+        last = Timestamp(offset.rollforward(last + offset))
+        return first, last
 
-    if not isinstance(offset, Tick):  # and first.time() != last.time():
+    else:  # and first.time() != last.time():
         # hack!
         first = first.normalize()
         last = last.normalize()

pandas/tseries/tests/test_resample.py

@@ -2297,6 +2297,17 @@ def test_upsample_daily_business_daily(self):
         expected = ts.asfreq('H', how='s').reindex(exp_rng)
         assert_series_equal(result, expected)
 
+    def test_resample_hourly_business_hourly(self):
+        ts = pd.Series(index=pd.date_range(start='2016-06-01 03:00:00',
+                                           end='2016-06-03 23:00:00',
+                                           freq='H'))
+        expected = pd.Series(index=pd.date_range(start='2016-05-31 17:00:00',
+                                                 end='2016-06-06 09:00:00',
+                                                 freq='BH'))
+
+        result = ts.resample('BH').mean()
+        assert_series_equal(result, expected)
+
     def test_resample_irregular_sparse(self):
         dr = date_range(start='1/1/2012', freq='5min', periods=1000)
         s = Series(np.array(100), index=dr)