Fix Series.__sub__ non-nano datetime64

doc/source/whatsnew/v0.22.0.txt

@@ -324,7 +324,7 @@ Reshaping
 Numeric
 ^^^^^^^
 
--
+- Bug in :func:`Series.__sub__` subtracting a non-nanosecond ``np.datetime64`` object from a ``Series`` gave incorrect results (:issue:`7996`)
 -
 -
 

pandas/core/ops.py

@@ -28,7 +28,7 @@
     is_datetimelike_v_numeric,
     is_integer_dtype, is_categorical_dtype,
     is_object_dtype, is_timedelta64_dtype,
-    is_datetime64_dtype, is_datetime64tz_dtype,
+    is_datetime64_dtype, is_datetime64tz_dtype, is_datetime64_ns_dtype,
     is_bool_dtype, is_datetimetz,
     is_list_like,
     is_scalar,
@@ -497,6 +497,11 @@ def _convert_to_array(self, values, name=None, other=None):
             elif not (isinstance(values, (np.ndarray, ABCSeries)) and
                       is_datetime64_dtype(values)):
                 values = libts.array_to_datetime(values)
+            elif (is_datetime64_dtype(values) and
+                  not is_datetime64_ns_dtype(values)):
+                # GH#7996 e.g. np.datetime64('2013-01-01') is datetime64[D]
+                values = values.astype('datetime64[ns]')
+
         elif inferred_type in ('timedelta', 'timedelta64'):
             # have a timedelta, convert to to ns here
             values = to_timedelta(values, errors='coerce', box=False)
@@ -671,7 +676,7 @@ def _arith_method_SERIES(op, name, str_rep, fill_zeros=None, default_axis=None,
     """
     def na_op(x, y):
         import pandas.core.computation.expressions as expressions
-
+        #
         try:
             result = expressions.evaluate(op, str_rep, x, y, **eval_kwargs)
         except TypeError:
@@ -688,9 +693,9 @@ def na_op(x, y):
                 raise TypeError("{typ} cannot perform the operation "
                                 "{op}".format(typ=type(x).__name__,
                                               op=str_rep))
-
+            #
             result, changed = maybe_upcast_putmask(result, ~mask, np.nan)
-
+        #
         result = missing.fill_zeros(result, x, y, name, fill_zeros)
         return result
 

pandas/tests/series/test_operators.py

@@ -28,6 +28,31 @@
 from .common import TestData
 
 
+class TestDatetimeLikeArithmetic(object):
+    def test_sub_datetime64_not_ns(self):
+        # GH#7996
+        ser = Series(date_range('20130101', periods=3))
+        dt64 = np.datetime64('2013-01-01')
+        assert dt64.dtype == 'datetime64[D]'
+        res = ser - dt64
+        expected = pd.Series([Timedelta(days=0), Timedelta(days=1),
+                              Timedelta(days=2)])
+        tm.assert_series_equal(res, expected)
+
+        res = dt64 - ser
+        tm.assert_series_equal(res, -expected)
+
+        # check for DatetimeIndex and DataFrame while we're at it
+        dti = pd.DatetimeIndex(ser)
+        res = dti - dt64
+        tm.assert_index_equal(res, pd.Index(expected))
+
+        res = dt64 - dti
+        tm.assert_index_equal(res, pd.Index(-expected))
+
+        # TODO: This is still broken for ser.to_frame()
+
+
 class TestSeriesOperators(TestData):
 
     def test_series_comparison_scalars(self):