sum excludes rows where multi-index has nan

[soerenwolfers]

Code Sample

import pandas as pd
import numpy as np
df = pd.DataFrame({'ind':[np.nan,np.nan,'a','a'],'col':[0,1,2,3]}).set_index('ind')
df.sum(level='ind')

results in

     col
ind     
a    5

Problem description

df.sum ignores rows where any index column contains a np.nan.

Expected Output

     col
ind     
NaN   1
1.0    5

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor:
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: None.None

pandas: 0.24.2
pytest: None
pip: 19.0.3
setuptools: 41.0.1
Cython: 0.28.4
numpy: 1.15.4
scipy: 1.2.1
pyarrow: 0.14.0
xarray: None
IPython: 7.5.0
sphinx: 1.7.5
patsy: 0.5.0
dateutil: 2.8.0
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.3.2
pandas_gbq: None
pandas_datareader: None
gcsfs: None

[TomAugspurger]

Thanks for the report. sum(level=...) uses groupby internally, so this is most likely the same as #3729. I'll add your note as a comment over there.

[itamarst]

This still happens in 1.2.4 and master as of May 2021. It should probably be reopened. I will try to implement a fix.

[itamarst]

Ah, no, it is fixed, just need to do dropna=False in the groupby().