BUG: concat with empty dataframe with columns passed and nonempty dataframe coerces dtype to object · Issue #45637 · pandas-dev/pandas (original) (raw)

Pandas version checks

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• I have confirmed this bug exists on the latest version of pandas.
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Reproducible Example

import pandas as pd

pd.concat([pd.DataFrame(columns=['foo', 'bar']), pd.DataFrame({'foo': [1.0, 2.0], 'bar': [1.0, 2.0]})]).dtypes

Out[3]: foo object bar object dtype: object

Issue Description

When using concat with empty dataframe with columns argument passed, and a nonempty dataframe, the dtypes of the resulting dataframe are coerced to object.

Expected Behavior

I would expect the dtypes to be taken from the nonempty dataframe, as was the behavior in previous versions of pandas.
This issue can be avoided if dtypes are explicitly passed, which maybe is intentional, but still it is unexpected.

Pandas 1.3.5 behavior:

In [120]: pd.concat([pd.DataFrame(columns=['foo', 'bar']), pd.DataFrame({'foo': [1.0, 2.0], 'bar': [1.0, 2.0]})]).dtypes
     ...: 
Out[120]: 
foo    float64
bar    float64
dtype: object

Installed Versions

INSTALLED VERSIONS
------------------
commit           : bb1f651536508cdfef8550f93ace7849b00046ee
python           : 3.8.12.final.0
python-bits      : 64
OS               : Linux
OS-release       : 3.10.0-957.27.2.el7.x86_64
Version          : #1 SMP Mon Jul 29 17:46:05 UTC 2019
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.4.0
numpy            : 1.21.5
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.3.1
setuptools       : 60.5.0
Cython           : None
pytest           : 5.4.3
hypothesis       : None
sphinx           : 4.4.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.9.3
jinja2           : 2.11.3
IPython          : 8.0.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
fsspec           : None
gcsfs            : None
matplotlib       : 3.4.2
numba            : None
numexpr          : 2.8.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyreadstat       : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.3
sqlalchemy       : 1.4.31
tables           : 3.6.1
tabulate         : None
xarray           : 0.15.1
xlrd             : None
xlwt             : None
zstandard        : None