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Keywords {🔍}

categorical, red, green, blue, bug, sortfalse, groupby, data, issue, dangillet, color, pandas, respected, multiindex, grouping, mroeschke, sign, jan, feb, mar, apr, index, output, team, type, discussion, code, projects, keys, directions, month, sorted, added, samukweku, commented, ordered, navigation, pull, requests, actions, security, closed, description, confirmed, exists, import, colors, pddataframe, nprandomrandom, indexpdmultiindexfromproductmonths,

Topics {✒️}

type projects personal information bug discussion requires discussion comment metadata assignees categorical index ordered categorical data core team import pandas categorical index unordered categorical projects milestone bug exists 871417 problem description triage issue pandas sort=false names=['month' level month months = ['jan' categorical latest version master branch code sample copy-pastable import numpy original order color index api/perf reorder categoricals milestone relationships bug index=pd github issue sorted lexicographically multiindex colors = ['red' expected output df = pd grouping groupby ordered removed ['month' 'apr'] 'color' 'color'] index code action

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      headline:BUG: groupby with sort=False not respected for categorical data for MultiIndex with 2 grouping keys
      articleBody:- [x] I have checked that this issue has not already been reported. - [x] I have confirmed this bug exists on the latest version of pandas. - [ ] (optional) I have confirmed this bug exists on the master branch of pandas. --- #### Code Sample, a copy-pastable example ```python 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 ```python 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()`` <details> INSTALLED VERSIONS ------------------ commit : f00ed8f47020034e752baf0250483053340971b0 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 </details>
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      headline:BUG: groupby with sort=False not respected for categorical data for MultiIndex with 2 grouping keys
      articleBody:- [x] I have checked that this issue has not already been reported. - [x] I have confirmed this bug exists on the latest version of pandas. - [ ] (optional) I have confirmed this bug exists on the master branch of pandas. --- #### Code Sample, a copy-pastable example ```python 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 ```python 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()`` <details> INSTALLED VERSIONS ------------------ commit : f00ed8f47020034e752baf0250483053340971b0 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 </details>
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