TST: properly handle unit='ns' and object/int arrays

Author: jreback

pandas/io/tests/json/test_pandas.py

@@ -614,6 +614,7 @@ def test_convert_dates(self):
 
         df['foo'] = 1.
         json = df.to_json(date_unit='ns')
+
         result = read_json(json, convert_dates=False)
         expected = df.copy()
         expected['date'] = expected['date'].values.view('i8')

pandas/tslib.pyx

@@ -1989,6 +1989,11 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
 
     assert is_ignore or is_coerce or is_raise
 
+    if unit == 'ns':
+        if issubclass(values.dtype.type, np.integer):
+            return values.astype('M8[ns]')
+        return array_to_datetime(values.astype(object), errors=errors)
+
     m = cast_from_unit(None, unit)
 
     if is_raise:
@@ -2003,13 +2008,6 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
             iresult[mask] = 0
         except:
 
-            # we might have a directly convertible M8[ns]
-            if unit == 'ns':
-                try:
-                    return values.astype('M8[ns]')
-                except:
-                    pass
-
             # we have nulls embedded
             from pandas import isnull