Description
Pandas version checks
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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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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
Let's start with:
ser = pd.Series([1, 2, 3, 4, 5], name='foo')
df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 4, 5]}, index=[2,3,4])Issue Description
ser.value_counts:nameis from original Series,indexis unnameddf.value_counts:nameisNone,indexnames from columns of original DataFramedf.groupby('a')['b'].value_counts():nameisb, index names areaandbdf.groupby('a', as_index=False)['b'].value_counts(): new column is'count', index is a newRangeIndex
Expected Behavior
My suggestion is:
ser.value_counts:nameis'count',indexis name of original Seriesdf.value_counts:nameis'count',indexnames from columns of original DataFramedf.groupby('a')['b'].value_counts():nameis'count', index names areaandbdf.groupby('a', as_index=False)['b'].value_counts(): new column is'count', index is a newRangeIndex[same as now]
NOTE: if normalize=True, then replace 'count' with 'proportion'
Bug or API change?
Given that:
df.groupby('a')['b'].value_counts().reset_index()errorsdf.groupby('a')[['b']].value_counts().reset_index()anddf.groupby('a', as_index=False)[['b']].value_counts()don't matchmulti_idx.value_counts()doesn't preserve the multiindex's name anywhere
I'd be more inclined to consider it a bug and to make the change in 2.0
Installed Versions
INSTALLED VERSIONS
commit : a215264
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 2.0.0.dev0+550.ga215264d47
numpy : 1.23.3
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 59.8.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.6
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.6.0
numba : 0.56.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.8
pyarrow : 9.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.9.0
xlrd : 2.0.1
zstandard : 0.18.0
tzdata : None
None