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BUG - pd.concat with all Series on axis=1 ignores the names argument (Issue: 23490) #23499

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Merged
merged 6 commits into from
Nov 6, 2018
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BUG - pd.concat with all Series on axis=1 ignores the names argument (Issue: 23490) #23499

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f82d9f3
BUG - account for names when concating series on axis 1
sds9995 Nov 4, 2018
3346f7f
TST - add test to make sure names argument is accounted for when conc…
sds9995 Nov 4, 2018
8f0d8d8
DOC - update whats new
sds9995 Nov 4, 2018
de4be0b
DOC - reference issue associated with test
sds9995 Nov 4, 2018
a41a0d3
BUG - use set_names instead of .names=... to ensure original keys not…
sds9995 Nov 6, 2018
3e624e8
TST - break up test into its own testing method
sds9995 Nov 6, 2018
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DOC - reference issue associated with test
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sds9995 committed Nov 4, 2018
commit de4be0b7cfde0f56f2f3e360c68cc67e15ecb5f8
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.24.0.txt
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Expand Up @@ -933,7 +933,7 @@ Reshaping
^^^^^^^^^

- Bug in :func:`pandas.concat` when joining resampled DataFrames with timezone aware index (:issue:`13783`)
- Bug in :func:`pandas.concat` when joining only series the `names` argument of `concat` is no longer ignored (:issue:`23490`)
- Bug in :func:`pandas.concat` when joining only `Series` the `names` argument of `concat` is no longer ignored (:issue:`23490`)
- Bug in :meth:`Series.combine_first` with ``datetime64[ns, tz]`` dtype which would return tz-naive result (:issue:`21469`)
- Bug in :meth:`Series.where` and :meth:`DataFrame.where` with ``datetime64[ns, tz]`` dtype (:issue:`21546`)
- Bug in :meth:`Series.mask` and :meth:`DataFrame.mask` with ``list`` conditionals (:issue:`21891`)
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2 changes: 1 addition & 1 deletion pandas/tests/reshape/test_concat.py
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Expand Up @@ -1618,7 +1618,7 @@ def test_concat_series_axis1(self, sort=sort):
expected = DataFrame({'A': s, 'B': s2})
assert_frame_equal(result, expected)

# ensure names argument is not ignored on axis=1
# ensure names argument is not ignored on axis=1, #23490
s = Series([1, 2, 3])
s2 = Series([4, 5, 6])
result = concat([s, s2], axis=1, keys=['a', 'b'], names=['A'])
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