TST: pd.concat on two (or more) series produces all-NaN dataframe (#33728)

Author: simonjayhawkins

pandas/tests/reshape/test_concat.py

@@ -2768,3 +2768,37 @@ def test_concat_copy_index(test_series, axis):
  comb = concat([df, df], axis=axis, copy=True)
  assert comb.index is not df.index
  assert comb.columns is not df.columns
+
+
+def test_concat_multiindex_datetime_object_index():
+ # https://github.com/pandas-dev/pandas/issues/11058
+ s = Series(
+ ["a", "b"],
+ index=MultiIndex.from_arrays(
+ [[1, 2], Index([dt.date(2013, 1, 1), dt.date(2014, 1, 1)], dtype="object")],
+ names=["first", "second"],
+ ),
+ )
+ s2 = Series(
+ ["a", "b"],
+ index=MultiIndex.from_arrays(
+ [[1, 2], Index([dt.date(2013, 1, 1), dt.date(2015, 1, 1)], dtype="object")],
+ names=["first", "second"],
+ ),
+ )
+ expected = DataFrame(
+ [["a", "a"], ["b", np.nan], [np.nan, "b"]],
+ index=MultiIndex.from_arrays(
+ [
+ [1, 2, 2],
+ DatetimeIndex(
+ ["2013-01-01", "2014-01-01", "2015-01-01"],
+ dtype="datetime64[ns]",
+ freq=None,
+ ),
+ ],
+ names=["first", "second"],
+ ),
+ )
+ result = concat([s, s2], axis=1)
+ tm.assert_frame_equal(result, expected)