ENH/API: offsets now accepts datetime64

Author: sinhrks

doc/source/v0.14.1.txt

@@ -126,7 +126,7 @@ Enhancements
 
 
 
-
+- All offsets ``apply``, ``rollforward`` and ``rollback`` can now handle ``np.datetime64``, previously results in ``ApplyTypeError`` (:issue:`7452`)
 
 
 

pandas/tseries/offsets.py

@@ -45,6 +45,8 @@ def wrapper(self, other):
             return tslib.NaT
         if type(other) == date:
             other = datetime(other.year, other.month, other.day)
+        elif isinstance(other, np.datetime64):
+            other = as_timestamp(other)
 
         result = func(self, other)
 
@@ -555,20 +557,6 @@ def apply(self, other):
 
             return as_timestamp(result)
 
-        elif isinstance(other, np.datetime64):
-            date_in = other
-            np_day = date_in.astype('datetime64[D]')
-            np_time = date_in - np_day
-
-            np_incr_dt = np.busday_offset(np_day, self.n, roll=roll,
-                                  busdaycal=self.busdaycalendar)
-            result = np_incr_dt + np_time
-
-            if self.offset:
-                result = result + self.offset
-
-            return as_timestamp(result)
-
         elif isinstance(other, (timedelta, Tick)):
             return BDay(self.n, offset=self.offset + other,
                         normalize=self.normalize)

pandas/tseries/tests/test_offsets.py

@@ -222,19 +222,20 @@ def _check_nanofunc_works(self, offset, funcname, dt, expected):
         self.assertEqual(func(t1), expected)
 
     def test_apply(self):
-        dt = datetime(2011, 1, 1, 9, 0)
+        sdt = datetime(2011, 1, 1, 9, 0)
+        ndt = np.datetime64('2011-01-01 09:00Z')
 
         for offset in self.offset_types:
-            expected = self.expecteds[offset.__name__]
-
-            if offset == Nano:
-                self._check_nanofunc_works(offset, 'apply', dt, expected)
-            else:
-                self._check_offsetfunc_works(offset, 'apply', dt, expected)
+            for dt in [sdt, ndt]:
+                expected = self.expecteds[offset.__name__]
+                if offset == Nano:
+                    self._check_nanofunc_works(offset, 'apply', dt, expected)
+                else:
+                    self._check_offsetfunc_works(offset, 'apply', dt, expected)
 
-                expected = Timestamp(expected.date())
-                self._check_offsetfunc_works(offset, 'apply', dt, expected,
-                                             normalize=True)
+                    expected = Timestamp(expected.date())
+                    self._check_offsetfunc_works(offset, 'apply', dt, expected,
+                                                 normalize=True)
 
     def test_rollforward(self):
         expecteds = self.expecteds.copy()
@@ -261,17 +262,19 @@ def test_rollforward(self):
                       'Micro': Timestamp('2011-01-01 00:00:00')}
         norm_expected.update(normalized)
 
-        dt = datetime(2011, 1, 1, 9, 0)
-        for offset in self.offset_types:
-            expected = expecteds[offset.__name__]
+        sdt = datetime(2011, 1, 1, 9, 0)
+        ndt = np.datetime64('2011-01-01 09:00Z')
 
-            if offset == Nano:
-                self._check_nanofunc_works(offset, 'rollforward', dt, expected)
-            else:
-                self._check_offsetfunc_works(offset, 'rollforward', dt, expected)
-                expected = norm_expected[offset.__name__]
-                self._check_offsetfunc_works(offset, 'rollforward', dt, expected,
-                                             normalize=True)
+        for offset in self.offset_types:
+            for dt in [sdt, ndt]:
+                expected = expecteds[offset.__name__]
+                if offset == Nano:
+                    self._check_nanofunc_works(offset, 'rollforward', dt, expected)
+                else:
+                    self._check_offsetfunc_works(offset, 'rollforward', dt, expected)
+                    expected = norm_expected[offset.__name__]
+                    self._check_offsetfunc_works(offset, 'rollforward', dt, expected,
+                                                 normalize=True)
 
     def test_rollback(self):
         expecteds = {'BusinessDay': Timestamp('2010-12-31 09:00:00'),
@@ -315,18 +318,20 @@ def test_rollback(self):
                       'Micro': Timestamp('2011-01-01 00:00:00')}
         norm_expected.update(normalized)
 
-        dt = datetime(2011, 1, 1, 9, 0)
-        for offset in self.offset_types:
-            expected = expecteds[offset.__name__]
+        sdt = datetime(2011, 1, 1, 9, 0)
+        ndt = np.datetime64('2011-01-01 09:00Z')
 
-            if offset == Nano:
-                self._check_nanofunc_works(offset, 'rollback', dt, expected)
-            else:
-                self._check_offsetfunc_works(offset, 'rollback', dt, expected)
+        for offset in self.offset_types:
+            for dt in [sdt, ndt]:
+                expected = expecteds[offset.__name__]
+                if offset == Nano:
+                    self._check_nanofunc_works(offset, 'rollback', dt, expected)
+                else:
+                    self._check_offsetfunc_works(offset, 'rollback', dt, expected)
 
-                expected = norm_expected[offset.__name__]
-                self._check_offsetfunc_works(offset, 'rollback',
-                                             dt, expected, normalize=True)
+                    expected = norm_expected[offset.__name__]
+                    self._check_offsetfunc_works(offset, 'rollback',
+                                                 dt, expected, normalize=True)
 
     def test_onOffset(self):
 

vb_suite/timeseries.py

@@ -285,14 +285,33 @@ def date_range(start=None, end=None, periods=None, freq=None):
 setup = common_setup + """
 import datetime as dt
 import pandas as pd
+import numpy as np
 
 date = dt.datetime(2011,1,1)
+dt64 = np.datetime64('2011-01-01 09:00Z')
+
+day = pd.offsets.Day()
+year = pd.offsets.YearBegin()
 cday = pd.offsets.CustomBusinessDay()
 cme = pd.offsets.CustomBusinessMonthEnd()
 """
+timeseries_day_incr = Benchmark("date + day",setup)
+
+timeseries_day_apply = Benchmark("day.apply(date)",setup)
+
+timeseries_year_incr = Benchmark("date + year",setup)
+
+timeseries_year_apply = Benchmark("year.apply(date)",setup)
+
 timeseries_custom_bday_incr = \
     Benchmark("date + cday",setup)
 
+timeseries_custom_bday_apply = \
+    Benchmark("cday.apply(date)",setup)
+
+timeseries_custom_bday_apply_dt64 = \
+    Benchmark("cday.apply(dt64)",setup)
+
 # Increment by n
 timeseries_custom_bday_incr_n = \
     Benchmark("date + 10 * cday",setup)