Closed
Description
-
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
>>> pd.DataFrame({'a': [1,2], 'b': [3, 0]})
a b
0 1 3
1 2 0
>>> df = pd.DataFrame({'a': [1,2], 'b': [3, 0]})
>>> df
a b
0 1 3
1 2 0
>>> df.apply(lambda x: max(x['a'], x['b']), axis = 1)
0 3
1 2
dtype: int64
>>> df.head(0).apply(lambda x: max(x['a'], x['b']), axis = 1)
Empty DataFrame
Columns: [a, b]
Index: []
>>>
Problem description
When running .apply() to a dataframe, I'm expecting to get a pd.Series back to add as an additional column. If the dataframe is empty and I run .apply() on it, it will return a dataframe and I cannot add it as a column
Expected Output
Output of pd.show_versions()
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit : d9fff2792bf16178d4e450fe7384244e50635733
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 20.2.0
Version : Darwin Kernel Version 20.2.0: Wed Dec 2 20:39:59 PST 2020; root:xnu-7195.60.75~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.0
numpy : 1.19.1
pytz : 2020.5
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20201009
Cython : None
pytest : 6.2.1
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : 1.3.7
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.5
fastparquet : None
gcsfs : None
matplotlib : 3.3.0
numexpr : None
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : 2.0.0
pytables : None
pyxlsb : None
s3fs : 0.5.1
scipy : 1.5.2
sqlalchemy : 1.3.19
tables : None
tabulate : 0.8.7
xarray : None
xlrd : 1.2.0
xlwt : None
numba : 0.50.1
>>>[paste the output of pd.show_versions() here leaving a blank line after the details tag]