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Keywords {🔍}

foo, bar, transform, behavior, dfgroupbyactransformpdseriessortvalues, rhshadrach, ben, pandas, index, option, series, commented, result, issue, member, bug, expect, jbrockmendel, return, groupby, groups, apply, indexed, sign, sort, defined, isnt, team, author, aligning, docs, object, consistency, discussion, projects, doesnt, version, pddataframe, convertdtypes, dataframe, sortvalues, expected, added, case, type, words, current, edited, edits, original,

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api/behavior apply apply rhshadrach edits member map bug groupby personal information bug discussion requires discussion comment metadata assignees full intended op action regression functionality document casting behavior dataframe type difference public docs transform method returns type projects latest version core team triage issue api/behavior bug exists projects milestone 1 apply pandas pandas 1 5 closed issue range index main branch works properly expected output drop=true necessarily agree numpy array parenthetical remarks change meaning points immediately applies equally create inconsistencies 100% complete relationships expected behavior current behavior input index obvious series series form groups defined docs written assuming special cases github frame result object indexed equal df

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• Can you explain this?
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DiscussionForumPosting:
      context:https://schema.org
      headline:BUG: groupby transform doesn't respect Series index anymore
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python df = pd.DataFrame({ 'A': ['foo', 'bar', 'foo', 'bar', 'bar', 'foo', 'foo'], 'C': [2.1, 1.9, 3.6, 4.0, 1.9, 7.8, 2.8] }).convert_dtypes() print(df) A C 0 foo 2.1 1 bar 1.9 2 foo 3.6 3 bar 4.0 4 bar 1.9 5 foo 7.8 6 foo 2.8 # sort C within groups defined by A df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 3.6 3 4.0 4 1.9 5 7.8 6 2.8 ``` ### Issue Description Suppose I have the following DataFrame ``` df = pd.DataFrame({ 'A': ['foo', 'bar', 'foo', 'bar', 'bar', 'foo', 'foo'], 'C': [2.1, 1.9, 3.6, 4.0, 1.9, 7.8, 2.8] }).convert_dtypes() print(df) A C 0 foo 2.1 1 bar 1.9 2 foo 3.6 3 bar 4.0 4 bar 1.9 5 foo 7.8 6 foo 2.8 ``` I used to be able to sort `C`'s values within the groups defined by `A` like this ([proof](https://youtu.be/n681ajrAuVE?t=547)): ``` df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` (This was sometime around Pandas 1.0.0) However pandas 1.4.0 produces the following ``` df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 3.6 3 4.0 4 1.9 5 7.8 6 2.8 ``` It's as if the `sort_values()` function isn't even being applied. Note that `df.groupby('A')[['C']].transform(pd.Series.sort_values)` works properly. ``` df.groupby('A')[['C']].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` ### Expected Behavior I would expect `df.groupby('A')['C'].transform(pd.Series.sort_values)` to actually sort C's values within the groups defined by A (as it once did). My expected output in this example would be a Series like this. ``` C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` ### Installed Versions <details> INSTALLED VERSIONS ------------------ commit : bb1f651536508cdfef8550f93ace7849b00046ee python : 3.10.1.final.0 python-bits : 64 OS : Darwin OS-release : 21.2.0 Version : Darwin Kernel Version 21.2.0: Sun Nov 28 20:28:54 PST 2021; root:xnu-8019.61.5~1/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : None LOCALE : en_US.UTF-8 pandas : 1.4.0 numpy : 1.22.1 pytz : 2021.3 dateutil : 2.8.2 pip : 21.1.2 setuptools : 57.0.0 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 : 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 : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None </details>
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      headline:BUG: groupby transform doesn't respect Series index anymore
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python df = pd.DataFrame({ 'A': ['foo', 'bar', 'foo', 'bar', 'bar', 'foo', 'foo'], 'C': [2.1, 1.9, 3.6, 4.0, 1.9, 7.8, 2.8] }).convert_dtypes() print(df) A C 0 foo 2.1 1 bar 1.9 2 foo 3.6 3 bar 4.0 4 bar 1.9 5 foo 7.8 6 foo 2.8 # sort C within groups defined by A df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 3.6 3 4.0 4 1.9 5 7.8 6 2.8 ``` ### Issue Description Suppose I have the following DataFrame ``` df = pd.DataFrame({ 'A': ['foo', 'bar', 'foo', 'bar', 'bar', 'foo', 'foo'], 'C': [2.1, 1.9, 3.6, 4.0, 1.9, 7.8, 2.8] }).convert_dtypes() print(df) A C 0 foo 2.1 1 bar 1.9 2 foo 3.6 3 bar 4.0 4 bar 1.9 5 foo 7.8 6 foo 2.8 ``` I used to be able to sort `C`'s values within the groups defined by `A` like this ([proof](https://youtu.be/n681ajrAuVE?t=547)): ``` df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` (This was sometime around Pandas 1.0.0) However pandas 1.4.0 produces the following ``` df.groupby('A')['C'].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 3.6 3 4.0 4 1.9 5 7.8 6 2.8 ``` It's as if the `sort_values()` function isn't even being applied. Note that `df.groupby('A')[['C']].transform(pd.Series.sort_values)` works properly. ``` df.groupby('A')[['C']].transform(pd.Series.sort_values) C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` ### Expected Behavior I would expect `df.groupby('A')['C'].transform(pd.Series.sort_values)` to actually sort C's values within the groups defined by A (as it once did). My expected output in this example would be a Series like this. ``` C 0 2.1 1 1.9 2 2.8 3 1.9 4 4.0 5 3.6 6 7.8 ``` ### Installed Versions <details> INSTALLED VERSIONS ------------------ commit : bb1f651536508cdfef8550f93ace7849b00046ee python : 3.10.1.final.0 python-bits : 64 OS : Darwin OS-release : 21.2.0 Version : Darwin Kernel Version 21.2.0: Sun Nov 28 20:28:54 PST 2021; root:xnu-8019.61.5~1/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : None LOCALE : en_US.UTF-8 pandas : 1.4.0 numpy : 1.22.1 pytz : 2021.3 dateutil : 2.8.2 pip : 21.1.2 setuptools : 57.0.0 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 : 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 : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None </details>
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