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Groupby ignores groups that contain a np.nan in any group-defining column.
I'd understand (well, not really, but it would be slightly more sane) if groups were ignored that had np.nans in grouped columns, but it doesn't make any sense to me to ignore groups that have np.nans in group-defining columns.
Until this is fixed properly, does anyone have a quick and dirty fix for me?
Code Sample, a copy-pastable example if possible
results in
Problem description
Groupby ignores groups that contain a np.nan in any group-defining column.
I'd understand (well, not really, but it would be slightly more sane) if groups were ignored that had np.nans in grouped columns, but it doesn't make any sense to me to ignore groups that have np.nans in group-defining columns.
Until this is fixed properly, does anyone have a quick and dirty fix for me?
Expected Output
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
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