COMPAT: don't rely on dtype being False after numpy >= 1.13

closes pandas-dev#15199

Author: jreback

pandas/core/ops.py

@@ -441,21 +441,17 @@ def _convert_to_array(self, values, name=None, other=None):
         from pandas.tseries.timedeltas import to_timedelta
 
         ovalues = values
-        supplied_dtype = None
         if not is_list_like(values):
             values = np.array([values])
         # if this is a Series that contains relevant dtype info, then use this
         # instead of the inferred type; this avoids coercing Series([NaT],
         # dtype='datetime64[ns]') to Series([NaT], dtype='timedelta64[ns]')
-        elif (isinstance(values, pd.Series) and
-              (is_timedelta64_dtype(values) or is_datetime64_dtype(values))):
-            supplied_dtype = values.dtype
-        inferred_type = supplied_dtype or lib.infer_dtype(values)
+        inferred_type = lib.infer_dtype(values)
         if (inferred_type in ('datetime64', 'datetime', 'date', 'time') or
                 is_datetimetz(inferred_type)):
             # if we have a other of timedelta, but use pd.NaT here we
             # we are in the wrong path
-            if (supplied_dtype is None and other is not None and
+            if (other is not None and
                 (other.dtype in ('timedelta64[ns]', 'datetime64[ns]')) and
                     isnull(values).all()):
                 values = np.empty(values.shape, dtype='timedelta64[ns]')