BUG: DataFrame.join with categorical index results in unexpected reordering · Issue #47812 · pandas-dev/pandas (original) (raw)
Pandas version checks
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Reproducible Example
import pandas as pd ix = ["a", "b"] df1 = pd.DataFrame({"c1": ix}, index=pd.CategoricalIndex(ix, categories=ix)) df2 = pd.DataFrame({"c2": reversed(ix)}, index=pd.CategoricalIndex(reversed(ix), categories=reversed(ix))) result = df1.join(df2) print(result)
c1 c2
a a b
b b a
Note that using concat
doesn't have this problem:
result_concat = pd.concat([df1, df2], axis=1) print(result)
c1 c2
a a a
b b b
Issue Description
When joining frames that have equivalent categorical index dtypes but use different orders, a join
results in unexpected results.
Most notably the index is joined in the wrong order such that the results become out of sync.
Expected Behavior
I would expect the join to synchonize the categorical index such that the result would be:
Interestingly, this is the exact result I get when using the "join" functionality of "concat" (see example).
Installed Versions
INSTALLED VERSIONS
commit : e8093ba
python : 3.10.4.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-121-generic
Version : #137-Ubuntu SMP Wed Jun 15 13:33:07 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.3
numpy : 1.22.3
pytz : 2022.1
dateutil : 2.8.2
setuptools : 61.2.0
pip : 22.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : 1.3.5
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : None
matplotlib : None
numba : None
numexpr : 2.8.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None