BUG: Fix timezone-related indexing and plotting bugs (#27367)

Author: mroeschke

doc/source/whatsnew/v0.25.0.rst

@@ -1036,6 +1036,7 @@ Timezones
 - Bug in :func:`DataFrame.join` where joining a timezone aware index with a timezone aware column would result in a column of ``NaN`` (:issue:`26335`)
 - Bug in :func:`date_range` where ambiguous or nonexistent start or end times were not handled by the ``ambiguous`` or ``nonexistent`` keywords respectively (:issue:`27088`)
 - Bug in :meth:`DatetimeIndex.union` when combining a timezone aware and timezone unaware :class:`DatetimeIndex` (:issue:`21671`)
+- Bug when applying a numpy reduction function (e.g. :meth:`numpy.minimum`) to a timezone aware :class:`Series` (:issue:`15552`)
 
 Numeric
 ^^^^^^^
@@ -1096,7 +1097,7 @@ Indexing
 - Bug in setting a new value in a :class:`Series` with a :class:`Timedelta` object incorrectly casting the value to an integer (:issue:`22717`)
 - Bug in :class:`Series` setting a new key (``__setitem__``) with a timezone-aware datetime incorrectly raising ``ValueError`` (:issue:`12862`)
 - Bug in :meth:`DataFrame.iloc` when indexing with a read-only indexer (:issue:`17192`)
--
+- Bug in :class:`Series` setting an existing tuple key (``__setitem__``) with timezone-aware datetime values incorrectly raising ``TypeError`` (:issue:`20441`)
 
 Missing
 ^^^^^^^
@@ -1153,7 +1154,7 @@ Plotting
 - Bug in an error message in :meth:`DataFrame.plot`. Improved the error message if non-numerics are passed to :meth:`DataFrame.plot` (:issue:`25481`)
 - Bug in incorrect ticklabel positions when plotting an index that are non-numeric / non-datetime (:issue:`7612`, :issue:`15912`, :issue:`22334`)
 - Fixed bug causing plots of :class:`PeriodIndex` timeseries to fail if the frequency is a multiple of the frequency rule code (:issue:`14763`)
--
+- Fixed bug when plotting a :class:`DatetimeIndex` with ``datetime.timezone.utc`` timezone (:issue:`17173`)
 -
 -
 

pandas/core/series.py

@@ -1236,6 +1236,10 @@ def setitem(key, value):
 
  def _set_with_engine(self, key, value):
  values = self._values
+ if is_extension_array_dtype(values.dtype):
+ # The cython indexing engine does not support ExtensionArrays.
+ values[self.index.get_loc(key)] = value
+ return
  try:
  self.index._engine.set_value(values, key, value)
  return

pandas/plotting/_matplotlib/converter.py

@@ -324,9 +324,6 @@ def axisinfo(unit, axis):
 class PandasAutoDateFormatter(dates.AutoDateFormatter):
  def __init__(self, locator, tz=None, defaultfmt="%Y-%m-%d"):
  dates.AutoDateFormatter.__init__(self, locator, tz, defaultfmt)
- # matplotlib.dates._UTC has no _utcoffset called by pandas
- if self._tz is dates.UTC:
- self._tz._utcoffset = self._tz.utcoffset(None)
 
 
 class PandasAutoDateLocator(dates.AutoDateLocator):

pandas/tests/plotting/test_datetimelike.py

@@ -45,9 +45,10 @@ def teardown_method(self, method):
  tm.close()
 
  @pytest.mark.slow
- def test_ts_plot_with_tz(self):
- # GH2877
- index = date_range("1/1/2011", periods=2, freq="H", tz="Europe/Brussels")
+ def test_ts_plot_with_tz(self, tz_aware_fixture):
+ # GH2877, GH17173
+ tz = tz_aware_fixture
+ index = date_range("1/1/2011", periods=2, freq="H", tz=tz)
  ts = Series([188.5, 328.25], index=index)
  _check_plot_works(ts.plot)
 

pandas/tests/reductions/test_reductions.py

@@ -159,6 +159,15 @@ def test_same_tz_min_max_axis_1(self, op, expected_col):
  expected = df[expected_col].rename(None)
  tm.assert_series_equal(result, expected)
 
+ @pytest.mark.parametrize("func", ["maximum", "minimum"])
+ def test_numpy_reduction_with_tz_aware_dtype(self, tz_aware_fixture, func):
+ # GH 15552
+ tz = tz_aware_fixture
+ arg = pd.to_datetime(["2019"]).tz_localize(tz)
+ expected = Series(arg)
+ result = getattr(np, func)(expected, expected)
+ tm.assert_series_equal(result, expected)
+
 
 class TestIndexReductions:
  # Note: the name TestIndexReductions indicates these tests

pandas/tests/series/indexing/test_datetime.py

@@ -765,3 +765,14 @@ def test_round_nat(method, freq):
  expected = Series(pd.NaT)
  round_method = getattr(s.dt, method)
  assert_series_equal(round_method(freq), expected)
+
+
+def test_setitem_tuple_with_datetimetz():
+ # GH 20441
+ arr = date_range("2017", periods=4, tz="US/Eastern")
+ index = [(0, 1), (0, 2), (0, 3), (0, 4)]
+ result = Series(arr, index=index)
+ expected = result.copy()
+ result[(0, 1)] = np.nan
+ expected.iloc[0] = np.nan
+ assert_series_equal(result, expected)