BUG: groupby with sort=False not respected for categorical data for MultiIndex with 2 grouping keys · Issue #42482 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example

In [1]: import numpy as np ...: import pandas as pd

In [2]: months = ['Jan', 'Feb', 'Mar', 'Apr'] ...: colors = ['Red', 'Green', 'Blue'] ...: directions = ['Up', 'Down']

In [3]: df = pd.DataFrame( ...: np.random.random(24), ...: index=pd.MultiIndex.from_product([months, pd.CategoricalIndex(colors), directions], names=['month', 'color', 'direction']), ...: columns=['value'] ...: )

In [4]: df.groupby(['month', 'color'], sort=False).sum()
Out[4]: value month color
Apr Blue 1.369042 Green 1.430864 Red 0.346581 Feb Blue 1.068234 Green 0.888100 Red 0.708154 Jan Blue 1.119714 Green 0.731628 Red 0.624529 Mar Blue 0.605137 Green 1.400212 Red 0.871417

Problem description

When grouping two columns with categorical data and using sort=False, the groups are sorted anyway. If the index was not Categorical, then the output is not sorted as expected.

Expected Output

I was hoping to get this output

Jan Red 0.624529 Green 0.731628 Blue 1.119714 Feb Red 0.708154 Green 0.888100 Blue 1.068234 Mar Red 0.871417 Green 1.400212 Blue 0.605137 Apr Red 0.346581 Green 1.430864 Blue 1.369042

Output of pd.show_versions()

INSTALLED VERSIONS

commit : f00ed8f
python : 3.7.11.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-77-generic
Version : #86-Ubuntu SMP Thu Jun 17 02:35:03 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 1.3.0
numpy : 1.17.5
pytz : 2020.1
dateutil : 2.8.1
pip : 21.1.2
setuptools : 41.2.0
Cython : 0.29.21
pytest : 6.1.1
hypothesis : None
sphinx : 3.3.1
blosc : 1.8.3
feather : None
xlsxwriter : None
lxml.etree : 4.4.3
html5lib : None
pymysql : None
psycopg2 : 2.7.7 (dt dec pq3 ext lo64)
jinja2 : 2.10.3
IPython : 7.14.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : 0.4.1
gcsfs : None
matplotlib : 3.1.3
numexpr : None
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : 0.51.2