BUG: Inconsistent behavior of index values for DataFrame.apply and Series.apply (original) (raw)

• 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.

Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

import pandas as pd pdf = pd.DataFrame([[4, 9]] * 3, columns=['A', 'B']) pdf.apply(["sum", lambda df: df.sum(), lambda df: df.sum()]) # lambdas have postfix 0, 1 ... A B sum 12 27 12 27 12 27 s = pd.Series([4] * 3) s.apply(["sum", lambda df: df.sum(), lambda df: df.sum()]) # lambdas have not postfix 0, 1 ... sum 12 12 12 dtype: int64

Problem description

Could anyone explain please? Is it normal behavior? Why DataFrame's index has postfix for lambdas, but Series's index hasn't. The same behavior is observed for agg. There is no such behavior in pandas==1.0.5.

Output of pd.show_versions()

Details

pandas : 1.1.1
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.3
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None