PERF: vectorized DateOffset with months

Author: chris-b1

doc/source/whatsnew/v0.17.0.txt

@@ -1056,6 +1056,7 @@ Performance Improvements
 - 2x improvement of ``Series.value_counts`` for float dtype (:issue:`10821`)
 - Enable ``infer_datetime_format`` in ``to_datetime`` when date components do not have 0 padding (:issue:`11142`)
 - Regression from 0.16.1 in constructing ``DataFrame`` from nested dictionary (:issue:`11084`)
+- Performance improvements in addition/subtraction operations for ``DateOffset`` with ``Series`` or ``DatetimeIndex``  (issue:`10744`, :issue:`11205`)
 
 .. _whatsnew_0170.bug_fixes:
 

pandas/tseries/offsets.py

@@ -261,16 +261,12 @@ def apply_index(self, i):
         # relativedelta/_offset path only valid for base DateOffset
         if (self._use_relativedelta and
             set(self.kwds).issubset(relativedelta_fast)):
+
             months = ((self.kwds.get('years', 0) * 12
                         + self.kwds.get('months', 0)) * self.n)
             if months:
-                base = (i.to_period('M') + months).to_timestamp()
-                time = i.to_perioddelta('D')
-                days = i.to_perioddelta('M') - time
-                # minimum prevents month-end from wrapping
-                day_offset = np.minimum(days,
-                                        to_timedelta(base.days_in_month - 1, unit='D'))
-                i = base + day_offset + time
+                shifted = tslib.shift_months(i.asi8, months)
+                i = i._shallow_copy(shifted)
 
             weeks = (self.kwds.get('weeks', 0)) * self.n
             if weeks:
@@ -1081,7 +1077,9 @@ def apply(self, other):
 
     @apply_index_wraps
     def apply_index(self, i):
-        return self._end_apply_index(i, 'M')
+        months = self.n - 1 if self.n >= 0 else self.n
+        shifted = tslib.shift_months(i.asi8, months, 'end')
+        return i._shallow_copy(shifted)
 
     def onOffset(self, dt):
         if self.normalize and not _is_normalized(dt):
@@ -1106,7 +1104,9 @@ def apply(self, other):
 
     @apply_index_wraps
     def apply_index(self, i):
-        return self._beg_apply_index(i, 'M')
+        months = self.n + 1 if self.n < 0 else self.n
+        shifted = tslib.shift_months(i.asi8, months, 'start')
+        return i._shallow_copy(shifted)
 
     def onOffset(self, dt):
         if self.normalize and not _is_normalized(dt):

pandas/tseries/tests/test_timeseries.py

@@ -2565,32 +2565,32 @@ def test_datetime64_with_DateOffset(self):
         for klass, assert_func in zip([Series, DatetimeIndex],
                                       [self.assert_series_equal,
                                        tm.assert_index_equal]):
-            s = klass(date_range('2000-01-01', '2000-01-31'))
+            s = klass(date_range('2000-01-01', '2000-01-31'), name='a')
             result = s + pd.DateOffset(years=1)
             result2 = pd.DateOffset(years=1) + s
-            exp = klass(date_range('2001-01-01', '2001-01-31'))
+            exp = klass(date_range('2001-01-01', '2001-01-31'), name='a')
             assert_func(result, exp)
             assert_func(result2, exp)
 
             result = s - pd.DateOffset(years=1)
-            exp = klass(date_range('1999-01-01', '1999-01-31'))
+            exp = klass(date_range('1999-01-01', '1999-01-31'), name='a')
             assert_func(result, exp)
 
             s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
-                       pd.Timestamp('2000-02-15', tz='US/Central')])
+                       pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
             result = s + pd.offsets.Day()
             result2 = pd.offsets.Day() + s
             exp = klass([Timestamp('2000-01-16 00:15:00', tz='US/Central'),
-                         Timestamp('2000-02-16', tz='US/Central')])
+                         Timestamp('2000-02-16', tz='US/Central')], name='a')
             assert_func(result, exp)
             assert_func(result2, exp)
 
             s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
-                       pd.Timestamp('2000-02-15', tz='US/Central')])
+                       pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
             result = s + pd.offsets.MonthEnd()
             result2 = pd.offsets.MonthEnd() + s
             exp = klass([Timestamp('2000-01-31 00:15:00', tz='US/Central'),
-                         Timestamp('2000-02-29', tz='US/Central')])
+                         Timestamp('2000-02-29', tz='US/Central')], name='a')
             assert_func(result, exp)
             assert_func(result2, exp)
 

pandas/tseries/tests/test_tslib.py

@@ -949,6 +949,17 @@ def compare_local_to_utc(tz_didx, utc_didx):
                                   tslib.maybe_get_tz('Asia/Tokyo'))
         self.assert_numpy_array_equal(result, np.array([tslib.iNaT], dtype=np.int64))
 
+    def test_shift_months(self):
+        s = DatetimeIndex([Timestamp('2000-01-05 00:15:00'), Timestamp('2000-01-31 00:23:00'),
+                           Timestamp('2000-01-01'), Timestamp('2000-02-29'), Timestamp('2000-12-31')])
+        for years in [-1, 0, 1]:
+            for months in [-2, 0, 2]:
+                actual = DatetimeIndex(tslib.shift_months(s.asi8, years * 12 + months))
+                expected = DatetimeIndex([x + offsets.DateOffset(years=years, months=months) for x in s])
+                tm.assert_index_equal(actual, expected)
+
+
+
 class TestTimestampOps(tm.TestCase):
     def test_timestamp_and_datetime(self):
         self.assertEqual((Timestamp(datetime.datetime(2013, 10, 13)) - datetime.datetime(2013, 10, 12)).days, 1)

pandas/tslib.pyx

@@ -3847,6 +3847,7 @@ def get_time_micros(ndarray[int64_t] dtindex):
 
     return micros
 
+
 @cython.wraparound(False)
 def get_date_field(ndarray[int64_t] dtindex, object field):
     '''
@@ -4386,6 +4387,75 @@ cpdef normalize_date(object dt):
         raise TypeError('Unrecognized type: %s' % type(dt))
 
 
+cdef inline int _year_add_months(pandas_datetimestruct dts,
+                                 int months):
+    '''new year number after shifting pandas_datetimestruct number of months'''
+    return dts.year + (dts.month + months - 1) / 12
+
+cdef inline int _month_add_months(pandas_datetimestruct dts,
+                                  int months):
+    '''new month number after shifting pandas_datetimestruct number of months'''
+    cdef int new_month = (dts.month + months) % 12
+    return 12 if new_month == 0 else new_month
+
+@cython.wraparound(False)
+def shift_months(int64_t[:] dtindex, int months, object day=None):
+    '''
+    Given an int64-based datetime index, shift all elements
+    specified number of months using DateOffset semantics
+
+    day: {None, 'start', 'end'}
+       * None: day of month
+       * 'start' 1st day of month
+       * 'end' last day of month
+    '''
+    cdef:
+        Py_ssize_t i
+        int days_in_month
+        pandas_datetimestruct dts
+        int count = len(dtindex)
+        int64_t[:] out = np.empty(count, dtype='int64')
+
+    for i in range(count):
+        if dtindex[i] == NPY_NAT:
+            out[i] = NPY_NAT
+        else:
+            pandas_datetime_to_datetimestruct(dtindex[i], PANDAS_FR_ns, &dts)
+
+            if day is None:
+                dts.year = _year_add_months(dts, months)
+                dts.month = _month_add_months(dts, months)
+                #prevent day from wrapping around month end
+                days_in_month = days_per_month_table[is_leapyear(dts.year)][dts.month-1]
+                dts.day = min(dts.day, days_in_month)
+            elif day == 'start':
+                dts.year = _year_add_months(dts, months)
+                dts.month = _month_add_months(dts, months)
+
+                # offset semantics - when subtracting if at the start anchor
+                # point, shift back by one more month
+                if months <= 0 and dts.day == 1:
+                    dts.year = _year_add_months(dts, -1)
+                    dts.month = _month_add_months(dts, -1)
+                else:
+                    dts.day = 1
+            elif day == 'end':
+                days_in_month = days_per_month_table[is_leapyear(dts.year)][dts.month-1]
+                dts.year = _year_add_months(dts, months)
+                dts.month = _month_add_months(dts, months)
+
+                # similar semantics - when adding shift forward by one
+                # month if already at an end of month
+                if months >= 0 and dts.day == days_in_month:
+                    dts.year = _year_add_months(dts, 1)
+                    dts.month = _month_add_months(dts, 1)
+
+                days_in_month = days_per_month_table[is_leapyear(dts.year)][dts.month-1]
+                dts.day = days_in_month
+
+            out[i] = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
+    return np.asarray(out)
+
 #----------------------------------------------------------------------
 # Don't even ask