API: Named aggregations for groupby.transform()

[ghost]

Code Sample, a copy-pastable example if possible

In [2]: df = pd.DataFrame({
   ...:     'A': [1, 1, 2, 2, 3, 3],
   ...:     'B': [4, 5, 6, 7, 8, 9]
   ...: })

In [3]: df
Out[3]:
   A  B
0  1  4
1  1  5
2  2  6
3  2  7
4  3  8
5  3  9

In [4]: df.groupby('A').agg(maximum=('B', 'max'))
Out[4]:
   maximum
A
1        5
2        7
3        9

In [5]: df.groupby('A').transform(maximum=('B', 'max'))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-10080a262c70> in <module>
----> 1 df.groupby('A').transform(maximum=('B', 'max'))

TypeError: transform() missing 1 required positional argument: 'func'

In [6]: df['maximum'] = df.groupby('A')['B'].transform('max')

In [7]: df
Out[7]:
   A  B  maximum
0  1  4        5
1  1  5        5
2  2  6        7
3  2  7        7
4  3  8        9
5  3  9        9

Problem description

Named aggregation streamlines the process of creating columns as a result of groupby.agg(). A similar (identical?) API for groupby.transform() would provide the same benefit when creating new columns from groupby.transform().

This issue may be related to #28380.

Expected Output

In [2]: df = pd.DataFrame({
   ...:     'A': [1, 1, 2, 2, 3, 3],
   ...:     'B': [4, 5, 6, 7, 8, 9]
   ...: })

In [3]: df.groupby('A').transform(maximum=('B', 'max'))
Out[3]:
   A  B  maximum
0  1  4        5
1  1  5        5
2  2  6        7
3  2  7        7
4  3  8        9
5  3  9        9

Output of pd.show_versions()

In [8]: pd.show_versions()
C:\Users\dwales\AppData\Local\Continuum\anaconda3\lib\site-packages\fastparquet\dataframe.py:5: FutureWarning: pandas.core.index is deprecated and will be removed in a future version. The public classes are available in the top-level namespace.
from pandas.core.index import CategoricalIndex, RangeIndex, Index, MultiIndex

INSTALLED VERSIONS

commit : None
python : 3.7.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None

pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.2.0.post20200210
Cython : 0.29.15
pytest : 5.3.5
hypothesis : 5.4.1
sphinx : 2.4.0
blosc : None
feather : None
xlsxwriter : 1.2.7
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.5.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.13.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : 0.8.3
xarray : 0.15.0
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.7
numba : 0.48.0

[mroeschke]

Thanks for the request but it appears this hasn't gotten traction in a while so closing