BUG: Series groupby with by as Series raises FutureWarning

[jsignell]

• I have checked that this issue has not already been reported.

• 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.

---

I ran into this when testing dask against pandas nightly builds. dask/dask#7710

Code Sample, a copy-pastable example

import pandas as pd
df = pd.DataFrame(
    {"a": [1, 2, 6, 4, 4, 6, 4, 3, 7], "b": [4, 2, 7, 3, 3, 1, 1, 1, 2]},
    index=[0, 1, 3, 5, 6, 8, 9, 9, 9],
)
df.a.groupby(df.b).sum()

Problem description

According to the series groupby docstring, I should be able to groupby series objects, but I get a FutureWarning

/home/julia/conda/envs/dask-upstream/lib/python3.8/site-packages/pandas/core/indexes/base.py:3372: FutureWarning: Promotion of numbers and bools to strings is deprecated. In the future, code such as `np.concatenate((['string'], [0]))` will raise an error, while `np.asarray(['string', 0])` will return an array with `dtype=object`.  To avoid the warning while retaining a string result use `dtype='U'` (or 'S').  To get an array of Python objects use `dtype=object`. (Warning added in NumPy 1.21)
  return self._engine.get_loc(casted_key)

Expected Output

When I call .tolist() on the series before passing it as by I get the expected result:

df.a.groupby(df.b.tolist()).sum()

Output of pd.show_versions()

INSTALLED VERSIONS

commit : e7c1ef7
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-72-generic
Version : #80~18.04.1-Ubuntu SMP Mon Apr 12 23:26:25 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.0.dev0+1738.ge7c1ef71d8
numpy : 1.22.0.dev0+4.gb283e1632
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.2
setuptools : 46.1.3
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.23.1
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 2021.05.0+16.g07df543
fastparquet : 0.6.3
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 4.0.0
pyxlsb : None
s3fs : 2021.05.0
scipy : 1.6.3
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : None
xarray : 0.18.2
xlrd : None
xlwt : None
numba : 0.53.1

[Lokeshrathi]

Hey @jsignell I ran the above code and got the results without any future warning.
no changes were done

pandas : 1.1.3
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.4
setuptools : 50.3.1.post20201107
Cython : 0.29.21
python : 3.8.5.final.0
python-bits : 64

Are you saying this is a issue for the latest pandas version?

[jsignell]

This is on the latest nightly build of pandas so pandas : 1.3.0.dev0+1738.ge7c1ef71d8

[mzeitlin11]

Probably same issue as #41632?

[mzeitlin11]

Closing as this is being tracked in #41632