Description
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
import pandas as pd
df = pd.DataFrame(
[[1,2,3,4],[5,6,7,8]],
columns=pd.MultiIndex.from_product(
[[0,1], ['foo','bar']],
names=['x', 'y']
)
)
after_groupby = df.groupby(df.index).ffill()
print(f"original dataframe:\n{df}\n")
print(f"result of groupby().ffill():\n{after_groupby}\n")
print(f"original dataframe columns.names:\n{df.columns.names}\n")
print(f"columns.names after groupby().ffill():\n{after_groupby.columns.names}\n")Actual output
original dataframe:
x 0 1
y foo bar foo bar
0 1 2 3 4
1 5 6 7 8
result of groupby().ffill():
0 1
foo bar foo bar
0 1 2 3 4
1 5 6 7 8
original dataframe columns.names:
['x', 'y']
columns.names after groupby().ffill():
[None, None]
Expected output
original dataframe:
x 0 1
y foo bar foo bar
0 1 2 3 4
1 5 6 7 8
result of groupby().ffill():
x 0 1
y foo bar foo bar
0 1 2 3 4
1 5 6 7 8
original dataframe columns.names:
['x', 'y']
columns.names after groupby().ffill():
['x', 'y']
Problem description
Calling groupby().ffill() on a DataFrame with a MultiIndex column index strips the names attribute of the column index. The above shows the trivial case of groupby(df.index), but I have also found it to occur with nontrivial by arguments (e.g. grouping a DatetimeIndex by dates).
This is obviously unexpected and undesirable.
Output of pd.show_versions()
I have observed this bug on WSL with Python 3.6 and pandas 1.1.5, as well as an M1 MacBook Air with the latest available M1-native pandas version from conda. The details of the latter are below.
INSTALLED VERSIONS
commit : 2cb9652
python : 3.9.2.final.0
python-bits : 64
OS : Darwin
OS-release : 20.3.0
Version : Darwin Kernel Version 20.3.0: Thu Jan 21 00:06:51 PST 2021; root:xnu-7195.81.3~1/RELEASE_ARM64_T8101
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.2.4
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.6.0.post20210108
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.0
IPython : 7.23.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None