BUG: Bug in tz-conversions with an ambiguous time and .dt accessors, #11295

doc/source/whatsnew/v0.17.1.txt

@@ -55,8 +55,12 @@ Bug Fixes
 
 - Bug in ``.to_latex()`` output broken when the index has a name (:issue: `10660`)
 - Bug in ``HDFStore.append`` with strings whose encoded length exceded the max unencoded length (:issue:`11234`)
+
 - Bug in ``HDFStore.select`` when comparing with a numpy scalar in a where clause (:issue:`11283`)
 
+- Bug in tz-conversions with an ambiguous time and ``.dt`` accessors (:issues:`11295`)
+
+
 
 
 

pandas/tests/test_index.py

@@ -3348,6 +3348,15 @@ def test_construction_with_alt(self):
         i2 = DatetimeIndex(i.tz_localize(None).asi8, dtype=i.dtype, tz=i.dtype.tz)
         self.assert_index_equal(i, i2)
 
+        # localize into the provided tz
+        i2 = DatetimeIndex(i.tz_localize(None).asi8, tz='UTC')
+        expected = i.tz_localize(None).tz_localize('UTC')
+        self.assert_index_equal(i2, expected)
+
+        i2 = DatetimeIndex(i, tz='UTC')
+        expected = i.tz_convert('UTC')
+        self.assert_index_equal(i2, expected)
+
         # incompat tz/dtype
         self.assertRaises(ValueError, lambda : DatetimeIndex(i.tz_localize(None).asi8, dtype=i.dtype, tz='US/Pacific'))
 

pandas/tests/test_series.py

@@ -224,6 +224,18 @@ def get_dir(s):
         results = get_dir(s)
         tm.assert_almost_equal(results, list(sorted(set(ok_for_period + ok_for_period_methods))))
 
+        # 11295
+        # ambiguous time error on the conversions
+        s = Series(pd.date_range('2015-01-01', '2016-01-01', freq='T'))
+        s = s.dt.tz_localize('UTC').dt.tz_convert('America/Chicago')
+        results = get_dir(s)
+        tm.assert_almost_equal(results, list(sorted(set(ok_for_dt + ok_for_dt_methods))))
+        expected = Series(pd.date_range('2015-01-01',
+                                        '2016-01-01',
+                                        freq='T',
+                                        tz='UTC').tz_convert('America/Chicago'))
+        tm.assert_series_equal(s, expected)
+
         # no setting allowed
         s = Series(date_range('20130101',periods=5,freq='D'))
         with tm.assertRaisesRegexp(ValueError, "modifications"):

pandas/tseries/common.py

@@ -45,8 +45,10 @@ def maybe_to_datetimelike(data, copy=False):
         raise TypeError("cannot convert an object of type {0} to a datetimelike index".format(type(data)))
 
     index = data.index
-    if is_datetime64_dtype(data.dtype) or is_datetime64tz_dtype(data.dtype):
+    if is_datetime64_dtype(data.dtype):
         return DatetimeProperties(DatetimeIndex(data, copy=copy, freq='infer'), index, name=data.name)
+    elif is_datetime64tz_dtype(data.dtype):
+        return DatetimeProperties(DatetimeIndex(data, copy=copy, freq='infer', ambiguous='infer'), index, name=data.name)
     elif is_timedelta64_dtype(data.dtype):
         return TimedeltaProperties(TimedeltaIndex(data, copy=copy, freq='infer'), index, name=data.name)
     else:

pandas/tseries/frequencies.py

@@ -851,10 +851,11 @@ def infer_freq(index, warn=True):
             raise TypeError("cannot infer freq from a non-convertible index type {0}".format(type(index)))
         index = index.values
 
-    try:
-        index = pd.DatetimeIndex(index)
-    except AmbiguousTimeError:
-        index = pd.DatetimeIndex(index.asi8)
+    if not isinstance(index, pd.DatetimeIndex):
+        try:
+            index = pd.DatetimeIndex(index)
+        except AmbiguousTimeError:
+            index = pd.DatetimeIndex(index.asi8)
 
     inferer = _FrequencyInferer(index, warn=warn)
     return inferer.get_freq()

pandas/tseries/index.py

@@ -194,7 +194,8 @@ def _join_i8_wrapper(joinf, **kwargs):
     _datetimelike_ops = ['year','month','day','hour','minute','second',
                          'weekofyear','week','dayofweek','weekday','dayofyear','quarter', 'days_in_month', 'daysinmonth',
                          'date','time','microsecond','nanosecond','is_month_start','is_month_end',
-                         'is_quarter_start','is_quarter_end','is_year_start','is_year_end','tz','freq']
+                         'is_quarter_start','is_quarter_end','is_year_start','is_year_end',
+                         'tz','freq']
     _is_numeric_dtype = False
 
 
@@ -269,14 +270,7 @@ def __new__(cls, data=None,
                                                      dayfirst=dayfirst,
                                                      yearfirst=yearfirst)
 
-        if is_datetimetz(data):
-            # extract the data whether a Series or Index
-            if isinstance(data, ABCSeries):
-                data = data._values
-            tz = data.tz
-            data = data.tz_localize(None, ambiguous='infer').values
-
-        if issubclass(data.dtype.type, np.datetime64):
+        if issubclass(data.dtype.type, np.datetime64) or is_datetimetz(data):
             if isinstance(data, ABCSeries):
                 data = data._values
             if isinstance(data, DatetimeIndex):