Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
print(pd.__version__) >>> '2.1.3'
df = pd.DataFrame(1, index=[0], columns=["test"])
s = pd.Series(1, index=[1], name="test")
pd.concat([df, s], axis="index")
>>> test 0
0 1.0 NaN
1 NaN 1.0
print(pd.concat([df, s.to_frame()], axis="index"))
>>> test
0 1
1 1Issue Description
Concatenating a DataFrame and a Series using axis="index" results in a new DataFrame with two columns, even if the column name is equal to the name of the series. One column is named "0".
Converting the Series to a DataFrame before calling pd.concat results in a DataFrame with only on column.
Expected Behavior
I expected, that there is no difference in the behavior and the result between these two examples. To me the DataFrame with two columns is not intuitive.
Installed Versions
INSTALLED VERSIONS
commit : 2a953cf
python : 3.10.9.final.0
python-bits : 64
OS : Linux
OS-release : 4.19.0-21-amd64
Version : #1 SMP Debian 4.19.249-2 (2022-06-30)
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.3
numpy : 1.26.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.6.0
pip : 23.0.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.11.0
pandas_datareader : None
bs4 : 4.11.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.7
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : 0.19.0
tzdata : 2023.3
qtpy : None
pyqt5 : None