API/BUG: DatetimeIndex correctly localizes integer data

doc/source/whatsnew/v0.24.0.txt

@@ -35,7 +35,7 @@ Datetimelike API Changes
 Other API Changes
 ^^^^^^^^^^^^^^^^^
 
--
+- :class:`DatetimeIndex` now accepts :class:`Int64Index` arguments as epoch timestamps (:issue:`20997`)
 -
 -
 
@@ -90,7 +90,7 @@ Categorical
 Datetimelike
 ^^^^^^^^^^^^
 
--
+- Bug in :class:`Index` with ``datetime64[ns, tz]`` dtype that did not localize integer data correctly (:issue:`20964`)
 -
 -
 

pandas/core/indexes/base.py

@@ -1164,6 +1164,10 @@ def astype(self, dtype, copy=True):
             return CategoricalIndex(self.values, name=self.name, dtype=dtype,
                                     copy=copy)
         try:
+            if is_datetime64tz_dtype(dtype):
+                from pandas.core.indexes.datetimes import DatetimeIndex
+                return DatetimeIndex(self.values, name=self.name, dtype=dtype,
+                                     copy=copy)
             return Index(self.values.astype(dtype, copy=copy), name=self.name,
                          dtype=dtype)
         except (TypeError, ValueError):

pandas/core/indexes/datetimes.py

@@ -394,57 +394,43 @@ def __new__(cls, data=None,
 
         # data must be Index or np.ndarray here
         if not (is_datetime64_dtype(data) or is_datetimetz(data) or
-                is_integer_dtype(data)):
+                is_integer_dtype(data) or lib.infer_dtype(data) == 'integer'):
             data = tools.to_datetime(data, dayfirst=dayfirst,
                                      yearfirst=yearfirst)
 
-        if issubclass(data.dtype.type, np.datetime64) or is_datetimetz(data):
-
-            if isinstance(data, DatetimeIndex):
-                if tz is None:
-                    tz = data.tz
-                elif data.tz is None:
-                    data = data.tz_localize(tz, ambiguous=ambiguous)
-                else:
-                    # the tz's must match
-                    if str(tz) != str(data.tz):
-                        msg = ('data is already tz-aware {0}, unable to '
-                               'set specified tz: {1}')
-                        raise TypeError(msg.format(data.tz, tz))
+        if isinstance(data, DatetimeIndex):
+            if tz is None:
+                tz = data.tz
+            elif data.tz is None:
+                data = data.tz_localize(tz, ambiguous=ambiguous)
+            else:
+                # the tz's must match
+                if str(tz) != str(data.tz):
+                    msg = ('data is already tz-aware {0}, unable to '
+                           'set specified tz: {1}')
+                    raise TypeError(msg.format(data.tz, tz))
 
-                subarr = data.values
+            subarr = data.values
 
-                if freq is None:
-                    freq = data.freq
-                    verify_integrity = False
-            else:
-                if data.dtype != _NS_DTYPE:
-                    subarr = conversion.ensure_datetime64ns(data)
-                else:
-                    subarr = data
+            if freq is None:
+                freq = data.freq
+                verify_integrity = False
+        elif issubclass(data.dtype.type, np.datetime64):
+            if data.dtype != _NS_DTYPE:
+                data = conversion.ensure_datetime64ns(data)
+            if tz is not None:
+                # Convert tz-naive to UTC
+                tz = timezones.maybe_get_tz(tz)
+                data = conversion.tz_localize_to_utc(data.view('i8'), tz,
+                                                     ambiguous=ambiguous)
+            subarr = data.view(_NS_DTYPE)
         else:
             # must be integer dtype otherwise
-            if isinstance(data, Int64Index):
-                raise TypeError('cannot convert Int64Index->DatetimeIndex')
+            # assume this data are epoch timestamps
             if data.dtype != _INT64_DTYPE:
-                data = data.astype(np.int64)
+                data = data.astype(np.int64, copy=False)
             subarr = data.view(_NS_DTYPE)
 
-        if isinstance(subarr, DatetimeIndex):
-            if tz is None:
-                tz = subarr.tz
-        else:
-            if tz is not None:
-                tz = timezones.maybe_get_tz(tz)
-
-                if (not isinstance(data, DatetimeIndex) or
-                        getattr(data, 'tz', None) is None):
-                    # Convert tz-naive to UTC
-                    ints = subarr.view('i8')
-                    subarr = conversion.tz_localize_to_utc(ints, tz,
-                                                           ambiguous=ambiguous)
-                subarr = subarr.view(_NS_DTYPE)
-
         subarr = cls._simple_new(subarr, name=name, freq=freq, tz=tz)
         if dtype is not None:
             if not is_dtype_equal(subarr.dtype, dtype):
@@ -806,8 +792,9 @@ def _mpl_repr(self):
 
     @cache_readonly
     def _is_dates_only(self):
+        """Return a boolean if we are only dates (and don't have a timezone)"""
         from pandas.io.formats.format import _is_dates_only
-        return _is_dates_only(self.values)
+        return _is_dates_only(self.values) and self.tz is None
 
     @property
     def _formatter_func(self):
@@ -1243,7 +1230,7 @@ def join(self, other, how='left', level=None, return_indexers=False,
         See Index.join
         """
         if (not isinstance(other, DatetimeIndex) and len(other) > 0 and
-            other.inferred_type not in ('floating', 'mixed-integer',
+            other.inferred_type not in ('floating', 'integer', 'mixed-integer',
                                         'mixed-integer-float', 'mixed')):
             try:
                 other = DatetimeIndex(other)
@@ -2081,8 +2068,9 @@ def normalize(self):
                        dtype='datetime64[ns, Asia/Calcutta]', freq=None)
         """
         new_values = conversion.date_normalize(self.asi8, self.tz)
-        return DatetimeIndex(new_values, freq='infer', name=self.name,
-                             tz=self.tz)
+        return DatetimeIndex(new_values,
+                             freq='infer',
+                             name=self.name).tz_localize(self.tz)
 
     @Substitution(klass='DatetimeIndex')
     @Appender(_shared_docs['searchsorted'])
@@ -2163,8 +2151,6 @@ def insert(self, loc, item):
         try:
             new_dates = np.concatenate((self[:loc].asi8, [item.view(np.int64)],
                                         self[loc:].asi8))
-            if self.tz is not None:
-                new_dates = conversion.tz_convert(new_dates, 'UTC', self.tz)
             return DatetimeIndex(new_dates, name=self.name, freq=freq,
                                  tz=self.tz)
         except (AttributeError, TypeError):
@@ -2202,8 +2188,6 @@ def delete(self, loc):
                 if (loc.start in (0, None) or loc.stop in (len(self), None)):
                     freq = self.freq
 
-        if self.tz is not None:
-            new_dates = conversion.tz_convert(new_dates, 'UTC', self.tz)
         return DatetimeIndex(new_dates, name=self.name, freq=freq, tz=self.tz)
 
     def tz_convert(self, tz):

pandas/tests/indexes/datetimes/test_astype.py

@@ -225,6 +225,16 @@ def _check_rng(rng):
         _check_rng(rng_eastern)
         _check_rng(rng_utc)
 
+    @pytest.mark.parametrize('tz, dtype', [
+        ['US/Pacific', 'datetime64[ns, US/Pacific]'],
+        [None, 'datetime64[ns]']])
+    def test_integer_index_astype_datetime(self, tz, dtype):
+        # GH 20997, 20964
+        val = [pd.Timestamp('2018-01-01', tz=tz).value]
+        result = pd.Index(val).astype(dtype)
+        expected = pd.DatetimeIndex(['2018-01-01'], tz=tz)
+        tm.assert_index_equal(result, expected)
+
 
 class TestToPeriod(object):
 

pandas/tests/indexes/datetimes/test_construction.py

@@ -1,8 +1,10 @@
-import pytest
+from datetime import timedelta
+from operator import attrgetter
+from functools import partial
 
+import pytest
 import pytz
 import numpy as np
-from datetime import timedelta
 
 import pandas as pd
 from pandas import offsets
@@ -26,25 +28,28 @@ def test_construction_caching(self):
                                                  freq='ns')})
         assert df.dttz.dtype.tz.zone == 'US/Eastern'
 
-    def test_construction_with_alt(self):
-
-        i = pd.date_range('20130101', periods=5, freq='H', tz='US/Eastern')
-        i2 = DatetimeIndex(i, dtype=i.dtype)
-        tm.assert_index_equal(i, i2)
-        assert i.tz.zone == 'US/Eastern'
-
-        i2 = DatetimeIndex(i.tz_localize(None).asi8, tz=i.dtype.tz)
-        tm.assert_index_equal(i, i2)
-        assert i.tz.zone == 'US/Eastern'
-
-        i2 = DatetimeIndex(i.tz_localize(None).asi8, dtype=i.dtype)
-        tm.assert_index_equal(i, i2)
-        assert i.tz.zone == 'US/Eastern'
-
-        i2 = DatetimeIndex(
-            i.tz_localize(None).asi8, dtype=i.dtype, tz=i.dtype.tz)
-        tm.assert_index_equal(i, i2)
-        assert i.tz.zone == 'US/Eastern'
+    @pytest.mark.parametrize('kwargs', [
+        {'tz': 'dtype.tz'},
+        {'dtype': 'dtype'},
+        {'dtype': 'dtype', 'tz': 'dtype.tz'}])
+    def test_construction_with_alt(self, kwargs, tz_aware_fixture):
+        tz = tz_aware_fixture
+        i = pd.date_range('20130101', periods=5, freq='H', tz=tz)
+        kwargs = {key: attrgetter(val)(i) for key, val in kwargs.items()}
+        result = DatetimeIndex(i, **kwargs)
+        tm.assert_index_equal(i, result)
+
+    @pytest.mark.parametrize('kwargs', [
+        {'tz': 'dtype.tz'},
+        {'dtype': 'dtype'},
+        {'dtype': 'dtype', 'tz': 'dtype.tz'}])
+    def test_construction_with_alt_tz_localize(self, kwargs, tz_aware_fixture):
+        tz = tz_aware_fixture
+        i = pd.date_range('20130101', periods=5, freq='H', tz=tz)
+        kwargs = {key: attrgetter(val)(i) for key, val in kwargs.items()}
+        result = DatetimeIndex(i.tz_localize(None).asi8, **kwargs)
+        expected = i.tz_localize(None).tz_localize('UTC').tz_convert(tz)
+        tm.assert_index_equal(result, expected)
 
         # localize into the provided tz
         i2 = DatetimeIndex(i.tz_localize(None).asi8, tz='UTC')
@@ -469,6 +474,19 @@ def test_constructor_with_non_normalized_pytz(self, tz):
         result = DatetimeIndex(['2010'], tz=non_norm_tz)
         assert pytz.timezone(tz) is result.tz
 
+    @pytest.mark.parametrize('klass', [Index, DatetimeIndex])
+    @pytest.mark.parametrize('box', [
+        np.array, partial(np.array, dtype=object), list])
+    @pytest.mark.parametrize('tz, dtype', [
+        ['US/Pacific', 'datetime64[ns, US/Pacific]'],
+        [None, 'datetime64[ns]']])
+    def test_constructor_with_int_tz(self, klass, box, tz, dtype):
+        # GH 20997, 20964
+        ts = Timestamp('2018-01-01', tz=tz)
+        result = klass(box([ts.value]), dtype=dtype)
+        expected = klass([ts])
+        tm.assert_index_equal(result, expected)
+
 
 class TestTimeSeries(object):
 

pandas/tests/indexes/test_base.py

@@ -402,26 +402,33 @@ def test_constructor_dtypes_to_timedelta(self, cast_index, vals):
             index = Index(vals)
             assert isinstance(index, TimedeltaIndex)
 
-    @pytest.mark.parametrize("values", [
-        # pass values without timezone, as DatetimeIndex localizes it
-        pd.date_range('2011-01-01', periods=5).values,
-        pd.date_range('2011-01-01', periods=5).asi8])
+    @pytest.mark.parametrize("attr, utc", [
+        ['values', False],
+        ['asi8', True]])
     @pytest.mark.parametrize("klass", [pd.Index, pd.DatetimeIndex])
-    def test_constructor_dtypes_datetime(self, tz_naive_fixture, values,
+    def test_constructor_dtypes_datetime(self, tz_naive_fixture, attr, utc,
                                          klass):
-        index = pd.date_range('2011-01-01', periods=5, tz=tz_naive_fixture)
+        # Test constructing with a datetimetz dtype
+        # .values produces numpy datetimes, so these are considered naive
+        # .asi8 produces integers, so these are considered epoch timestamps
+        index = pd.date_range('2011-01-01', periods=5)
+        arg = getattr(index, attr)
+        if utc:
+            index = index.tz_localize('UTC').tz_convert(tz_naive_fixture)
+        else:
+            index = index.tz_localize(tz_naive_fixture)
         dtype = index.dtype
 
-        result = klass(values, tz=tz_naive_fixture)
+        result = klass(arg, tz=tz_naive_fixture)
         tm.assert_index_equal(result, index)
 
-        result = klass(values, dtype=dtype)
+        result = klass(arg, dtype=dtype)
         tm.assert_index_equal(result, index)
 
-        result = klass(list(values), tz=tz_naive_fixture)
+        result = klass(list(arg), tz=tz_naive_fixture)
         tm.assert_index_equal(result, index)
 
-        result = klass(list(values), dtype=dtype)
+        result = klass(list(arg), dtype=dtype)
         tm.assert_index_equal(result, index)
 
     @pytest.mark.parametrize("attr", ['values', 'asi8'])