BUG: use more generic type inference for fast plotting (#15094)

xref #15073

Author: jreback

doc/source/whatsnew/v0.20.0.txt

@@ -248,6 +248,7 @@ Other API Changes
 - ``pd.read_csv()`` will now issue a ``ParserWarning`` whenever there are conflicting values provided by the ``dialect`` parameter and the user (:issue:`14898`)
 - ``pd.read_csv()`` will now raise a ``ValueError`` for the C engine if the quote character is larger than than one byte (:issue:`11592`)
 - ``inplace`` arguments now require a boolean value, else a ``ValueError`` is thrown (:issue:`14189`)
+- ``pandas.api.types.is_datetime64_ns_dtype`` will now report ``True`` on a tz-aware dtype, similar to ``pandas.api.types.is_datetime64_any_dtype``
 
 .. _whatsnew_0200.deprecations:
 

pandas/tests/types/test_dtypes.py

@@ -11,7 +11,8 @@
                                  is_datetime64tz_dtype, is_datetimetz,
                                  is_period_dtype, is_period,
                                  is_dtype_equal, is_datetime64_ns_dtype,
-                                 is_datetime64_dtype, is_string_dtype,
+                                 is_datetime64_dtype,
+                                 is_datetime64_any_dtype, is_string_dtype,
                                  _coerce_to_dtype)
 import pandas.util.testing as tm
 
@@ -132,8 +133,12 @@ def test_coerce_to_dtype(self):
                          DatetimeTZDtype('ns', 'Asia/Tokyo'))
 
     def test_compat(self):
-        self.assertFalse(is_datetime64_ns_dtype(self.dtype))
-        self.assertFalse(is_datetime64_ns_dtype('datetime64[ns, US/Eastern]'))
+        self.assertTrue(is_datetime64tz_dtype(self.dtype))
+        self.assertTrue(is_datetime64tz_dtype('datetime64[ns, US/Eastern]'))
+        self.assertTrue(is_datetime64_any_dtype(self.dtype))
+        self.assertTrue(is_datetime64_any_dtype('datetime64[ns, US/Eastern]'))
+        self.assertTrue(is_datetime64_ns_dtype(self.dtype))
+        self.assertTrue(is_datetime64_ns_dtype('datetime64[ns, US/Eastern]'))
         self.assertFalse(is_datetime64_dtype(self.dtype))
         self.assertFalse(is_datetime64_dtype('datetime64[ns, US/Eastern]'))
 

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 +809,38 @@ 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):
+
+        ts = pd.date_range('20130101', periods=3)
+        tsa = pd.date_range('20130101', periods=3, tz='US/Eastern')
+
+        self.assertTrue(is_datetime64_dtype('datetime64'))
+        self.assertTrue(is_datetime64_dtype('datetime64[ns]'))
+        self.assertTrue(is_datetime64_dtype(ts))
+        self.assertFalse(is_datetime64_dtype(tsa))
+
+        self.assertFalse(is_datetime64_ns_dtype('datetime64'))
+        self.assertTrue(is_datetime64_ns_dtype('datetime64[ns]'))
+        self.assertTrue(is_datetime64_ns_dtype(ts))
+        self.assertTrue(is_datetime64_ns_dtype(tsa))
+
+        self.assertTrue(is_datetime64_any_dtype('datetime64'))
+        self.assertTrue(is_datetime64_any_dtype('datetime64[ns]'))
+        self.assertTrue(is_datetime64_any_dtype(ts))
+        self.assertTrue(is_datetime64_any_dtype(tsa))
+
+        self.assertFalse(is_datetime64tz_dtype('datetime64'))
+        self.assertFalse(is_datetime64tz_dtype('datetime64[ns]'))
+        self.assertFalse(is_datetime64tz_dtype(ts))
+        self.assertTrue(is_datetime64tz_dtype(tsa))
+
+        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 +62,25 @@ 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(ts.to_pydatetime(), 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(Index([ts - Day(1), ts]).to_pydatetime(),
+                              None, None)
+        self.assertEqual(rs[1], xp)
+
     def test_conversion_float(self):
         decimals = 9
 

pandas/tseries/tests/test_timeseries.py

@@ -2404,7 +2404,7 @@ def test_to_datetime_tz_psycopg2(self):
         i = pd.DatetimeIndex([
             '2000-01-01 08:00:00+00:00'
         ], tz=psycopg2.tz.FixedOffsetTimezone(offset=-300, name=None))
-        self.assertFalse(is_datetime64_ns_dtype(i))
+        self.assertTrue(is_datetime64_ns_dtype(i))
 
         # tz coerceion
         result = pd.to_datetime(i, errors='coerce')

pandas/tseries/tools.py

@@ -309,7 +309,14 @@ def _convert_listlike(arg, box, format, name=None, tz=tz):
             arg = np.array(arg, dtype='O')
 
         # these are shortcutable
-        if is_datetime64_ns_dtype(arg):
+        if is_datetime64tz_dtype(arg):
+            if not isinstance(arg, DatetimeIndex):
+                return DatetimeIndex(arg, tz=tz, name=name)
+            if utc:
+                arg = arg.tz_convert(None).tz_localize('UTC')
+            return arg
+
+        elif is_datetime64_ns_dtype(arg):
             if box and not isinstance(arg, DatetimeIndex):
                 try:
                     return DatetimeIndex(arg, tz=tz, name=name)
@@ -318,13 +325,6 @@ def _convert_listlike(arg, box, format, name=None, tz=tz):
 
             return arg
 
-        elif is_datetime64tz_dtype(arg):
-            if not isinstance(arg, DatetimeIndex):
-                return DatetimeIndex(arg, tz=tz, name=name)
-            if utc:
-                arg = arg.tz_convert(None).tz_localize('UTC')
-            return arg
-
         elif unit is not None:
             if format is not None:
                 raise ValueError("cannot specify both format and unit")

pandas/types/common.py

@@ -187,8 +187,11 @@ def is_datetime64_ns_dtype(arr_or_dtype):
     try:
         tipo = _get_dtype(arr_or_dtype)
     except TypeError:
-        return False
-    return tipo == _NS_DTYPE
+        if is_datetime64tz_dtype(arr_or_dtype):
+            tipo = _get_dtype(arr_or_dtype.dtype)
+        else:
+            return False
+    return tipo == _NS_DTYPE or getattr(tipo, 'base', None) == _NS_DTYPE
 
 
 def is_timedelta64_ns_dtype(arr_or_dtype):