BUG: Apply ewm to GroupBy object results in duplicate index columns

[matteosantama]

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

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

import pandas as pd

pd.__version__
>>> '1.3.4'

numbers = [1, 2, 3, 4]
colors = ["green", "red", "blue"]
index = pd.MultiIndex.from_product([numbers, colors], names=["numbers", "colors"])
df = pd.DataFrame({"data": range(len(numbers) * len(colors))}, index=index)

df.groupby(level=["colors"]).mean()
>>>         data
colors      
blue     6.5
green    4.5
red      5.5

df.groupby(level=["colors"]).ewm(span=2).mean()
>>>                            data
colors numbers colors          
blue   1       blue    2.000000
       2       blue    4.250000
       3       blue    6.846154
       4       blue    9.650000
green  1       green   0.000000
       2       green   2.250000
       3       green   4.846154
       4       green   7.650000
red    1       red     1.000000
       2       red     3.250000
       3       red     5.846154
       4       red     8.650000

Issue Description

By adding an intermediary .ewm() step to the groupby operation, the resulting DataFrame has a duplicate index column.

Expected Behavior

I would expect consistent behavior whether I apply a .ewm transformation or not.

Installed Versions

INSTALLED VERSIONS

commit : 945c9ed
python : 3.8.12.final.0
python-bits : 64
OS : Darwin
OS-release : 21.1.0
Version : Darwin Kernel Version 21.1.0: Wed Oct 13 17:33:01 PDT 2021; root:xnu-8019.41.5~1/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.4
numpy : 1.20.0
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 56.0.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.4
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.30.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
fsspec : 2021.11.1
fastparquet : None
gcsfs : None
matplotlib : 3.5.0
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.11.1
scipy : 1.7.3
sqlalchemy : 1.4.27
tables : None
tabulate : 0.8.9
xarray : 0.20.1
xlrd : None
xlwt : None
numba : None

[phofl]

This is deliberate. See https://pandas.pydata.org/docs/whatsnew/v1.3.0.html#groupby-rolling-with-multiindex-no-longer-drops-levels-in-the-result and #44410