BUG: use more generic type inference for fast plotting

xref pandas-dev#15073

Author: jreback

pandas/tests/types/test_inference.py

@@ -22,6 +22,10 @@
 from pandas.types import inference
 from pandas.types.common import (is_timedelta64_dtype,
                                  is_timedelta64_ns_dtype,
+                                 is_datetime64_dtype,
+                                 is_datetime64_ns_dtype,
+                                 is_datetime64_any_dtype,
+                                 is_datetime64tz_dtype,
                                  is_number,
                                  is_integer,
                                  is_float,
@@ -805,6 +809,23 @@ def test_is_float(self):
         self.assertFalse(is_float(np.timedelta64(1, 'D')))
         self.assertFalse(is_float(Timedelta('1 days')))
 
+    def test_is_datetime_dtypes(self):
+        self.assertTrue(is_datetime64_dtype('datetime64'))
+        self.assertTrue(is_datetime64_dtype('datetime64[ns]'))
+
+        self.assertFalse(is_datetime64_ns_dtype('datetime64'))
+        self.assertTrue(is_datetime64_ns_dtype('datetime64[ns]'))
+
+        self.assertTrue(is_datetime64_any_dtype('datetime64'))
+        self.assertTrue(is_datetime64_any_dtype('datetime64[ns]'))
+
+        for tz in ['US/Eastern', 'UTC']:
+            dtype = 'datetime64[ns, {}]'.format(tz)
+            self.assertFalse(is_datetime64_dtype(dtype))
+            self.assertTrue(is_datetime64tz_dtype(dtype))
+            self.assertTrue(is_datetime64_ns_dtype(dtype))
+            self.assertTrue(is_datetime64_any_dtype(dtype))
+
     def test_is_timedelta(self):
         self.assertTrue(is_timedelta64_dtype('timedelta64'))
         self.assertTrue(is_timedelta64_dtype('timedelta64[ns]'))

pandas/tseries/tests/test_converter.py

@@ -3,10 +3,10 @@
 import nose
 
 import numpy as np
-from pandas import Timestamp, Period
+from pandas import Timestamp, Period, Index
 from pandas.compat import u
 import pandas.util.testing as tm
-from pandas.tseries.offsets import Second, Milli, Micro
+from pandas.tseries.offsets import Second, Milli, Micro, Day
 from pandas.compat.numpy import np_datetime64_compat
 
 try:
@@ -62,6 +62,21 @@ def test_conversion(self):
             np_datetime64_compat('2012-01-02 00:00:00+0000')]), None, None)
         self.assertEqual(rs[0], xp)
 
+        # we have a tz-aware date (constructed to that when we turn to utc it
+        # is the same as our sample)
+        ts = (Timestamp('2012-01-01')
+              .tz_localize('UTC')
+              .tz_convert('US/Eastern')
+              )
+        rs = self.dtc.convert(ts, None, None)
+        self.assertEqual(rs, xp)
+
+        rs = self.dtc.convert(Index([ts - Day(1), ts]), None, None)
+        self.assertEqual(rs[1], xp)
+
+        rs = self.dtc.convert(ts, None, None)
+        self.assertEqual(rs, xp)
+
     def test_conversion_float(self):
         decimals = 9
 

pandas/types/common.py

@@ -188,7 +188,7 @@ def is_datetime64_ns_dtype(arr_or_dtype):
         tipo = _get_dtype(arr_or_dtype)
     except TypeError:
         return False
-    return tipo == _NS_DTYPE
+    return tipo == _NS_DTYPE or getattr(tipo, 'base', None) == _NS_DTYPE
 
 
 def is_timedelta64_ns_dtype(arr_or_dtype):