BUG: Fixed merging on tz-aware

doc/source/whatsnew/v0.24.1.rst

@@ -23,6 +23,7 @@ Fixed Regressions
 - Bug in :meth:`DataFrame.itertuples` with ``records`` orient raising an ``AttributeError`` when the ``DataFrame`` contained more than 255 columns (:issue:`24939`)
 - Bug in :meth:`DataFrame.itertuples` orient converting integer column names to strings prepended with an underscore (:issue:`24940`)
 - Fixed regression in :class:`Index.intersection` incorrectly sorting the values by default (:issue:`24959`).
+- Fixed regression in :func:`merge` when merging an empty ``DataFrame`` with multiple timezone-aware columns on one of the timezone-aware columns (:issue:`25014`).
 
 .. _whatsnew_0241.enhancements:
 

pandas/core/internals/concat.py

@@ -335,8 +335,10 @@ def get_empty_dtype_and_na(join_units):
  elif 'category' in upcast_classes:
  return np.dtype(np.object_), np.nan
  elif 'datetimetz' in upcast_classes:
+ # GH-25014. We use NaT instead of iNaT, since this eventually
+ # ends up in DatetimeArray.take, which does not allow iNaT.
  dtype = upcast_classes['datetimetz']
- return dtype[0], tslibs.iNaT
+ return dtype[0], tslibs.NaT
  elif 'datetime' in upcast_classes:
  return np.dtype('M8[ns]'), tslibs.iNaT
  elif 'timedelta' in upcast_classes:

pandas/tests/reshape/merge/test_merge.py

@@ -616,6 +616,24 @@ def test_merge_on_datetime64tz(self):
  assert result['value_x'].dtype == 'datetime64[ns, US/Eastern]'
  assert result['value_y'].dtype == 'datetime64[ns, US/Eastern]'
 
+ def test_merge_on_datetime64tz_empty(self):
+ # https://github.com/pandas-dev/pandas/issues/25014
+ dtz = pd.DatetimeTZDtype(tz='UTC')
+ right = pd.DataFrame({'date': [pd.Timestamp('2018', tz=dtz.tz)],
+ 'value': [4.0],
+ 'date2': [pd.Timestamp('2019', tz=dtz.tz)]},
+ columns=['date', 'value', 'date2'])
+ left = right[:0]
+ result = left.merge(right, on='date')
+ expected = pd.DataFrame({
+ 'value_x': pd.Series(dtype=float),
+ 'date2_x': pd.Series(dtype=dtz),
+ 'date': pd.Series(dtype=dtz),
+ 'value_y': pd.Series(dtype=float),
+ 'date2_y': pd.Series(dtype=dtz),
+ }, columns=['value_x', 'date2_x', 'date', 'value_y', 'date2_y'])
+ tm.assert_frame_equal(result, expected)
+
  def test_merge_datetime64tz_with_dst_transition(self):
  # GH 18885
  df1 = pd.DataFrame(pd.date_range(