BUG: Fixed DataFrame.values for 1 column DataFrame

Author: TomAugspurger

doc/source/whatsnew/v0.24.0.rst

@@ -1314,6 +1314,7 @@ Datetimelike
 - Bug in :class:`DataFrame` with ``datetime64[ns]`` dtype subtracting ``np.datetime64`` object with non-nanosecond unit failing to convert to nanoseconds (:issue:`18874`, :issue:`22163`)
 - Bug in :class:`DataFrame` comparisons against ``Timestamp``-like objects failing to raise ``TypeError`` for inequality checks with mismatched types (:issue:`8932`, :issue:`22163`)
 - Bug in :class:`DataFrame` with mixed dtypes including ``datetime64[ns]`` incorrectly raising ``TypeError`` on equality comparisons (:issue:`13128`, :issue:`22163`)
+- Bug in :attr:`DataFrame.values` returning a :class:`DatetimeIndex` for a single-column ``DataFrame`` with was tz-aware datetime values. Now a 2-D :class:`numpy.ndarray` of :class:`Timestamp` objects is returned (:issue:`24024`)
 - Bug in :meth:`DataFrame.eq` comparison against ``NaT`` incorrectly returning ``True`` or ``NaN`` (:issue:`15697`, :issue:`22163`)
 - Bug in :class:`DatetimeIndex` subtraction that incorrectly failed to raise ``OverflowError`` (:issue:`22492`, :issue:`22508`)
 - Bug in :class:`DatetimeIndex` incorrectly allowing indexing with ``Timedelta`` object (:issue:`20464`)

pandas/core/internals/blocks.py

@@ -3006,9 +3006,11 @@ def get_values(self, dtype=None):
         # We added an asarray to BlockManager.as_array to work around this.
         values = self.values
         if is_object_dtype(dtype):
-            return (values._box_values(values._data)
-                    .reshape(self.values.shape))
-        return self.values
+            values = values._box_values(values._data)
+
+        if self.ndim == 2:
+            # Ensure that our shape is correct for DataFrame.
+            return values.reshape(1, -1)
 
     def _to_json_values(self):
         from pandas import DatetimeIndex

pandas/tests/frame/test_timezones.py

@@ -9,13 +9,48 @@
 import numpy as np
 
 import pandas.util.testing as tm
+import pandas as pd
 from pandas.compat import lrange
 from pandas.core.indexes.datetimes import date_range
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas import Series, DataFrame
 
 
 class TestDataFrameTimezones(object):
+
+    def test_frame_values_with_tz(self):
+        tz = "US/Central"
+        df = DataFrame({"A": date_range('2000', periods=4, tz=tz)})
+        result = df.values
+        expected = np.array([
+            [pd.Timestamp('2000-01-01', tz=tz)],
+            [pd.Timestamp('2000-01-02', tz=tz)],
+            [pd.Timestamp('2000-01-03', tz=tz)],
+            [pd.Timestamp('2000-01-04', tz=tz)],
+        ])
+        tm.assert_numpy_array_equal(result, expected)
+
+        # two columns, homogenous
+
+        df = df.assign(B=df.A)
+        result = df.values
+        expected = np.concatenate([expected, expected], axis=1)
+        tm.assert_numpy_array_equal(result, expected)
+
+        # three columns, heterogenous
+        est = "US/Eastern"
+        df = df.assign(C=df.A.dt.tz_convert(est))
+
+        new = np.array([
+            [pd.Timestamp('2000-01-01T01:00:00', tz=est)],
+            [pd.Timestamp('2000-01-02T01:00:00', tz=est)],
+            [pd.Timestamp('2000-01-03T01:00:00', tz=est)],
+            [pd.Timestamp('2000-01-04T01:00:00', tz=est)],
+        ])
+        expected = np.concatenate([expected, new], axis=1)
+        result = df.values
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_frame_from_records_utc(self):
         rec = {'datum': 1.5,
                'begin_time': datetime(2006, 4, 27, tzinfo=pytz.utc)}

pandas/tests/io/json/test_pandas.py

@@ -1013,7 +1013,6 @@ def test_tz_is_utc(self):
         dt = ts.to_pydatetime()
         assert dumps(dt, iso_dates=True) == exp
 
-    @pytest.mark.xfail(reason="TODO-json")
     def test_tz_range_is_utc(self):
         from pandas.io.json import dumps