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BUG: pd.DataFrame.sum with min_count changes dtype if result contains NaNs #46947

Closed
2 of 3 tasks
kdebrab opened this issue May 5, 2022 · 2 comments · Fixed by #47091
Closed
2 of 3 tasks

BUG: pd.DataFrame.sum with min_count changes dtype if result contains NaNs #46947

kdebrab opened this issue May 5, 2022 · 2 comments · Fixed by #47091
Labels
Bug Dtype Conversions Unexpected or buggy dtype conversions Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Reduction Operations sum, mean, min, max, etc.
Milestone
1.5

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@kdebrab
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kdebrab commented May 5, 2022 •
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Pandas version checks

  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

>>> import numpy as np
>>> import pandas as pd
>>> df = pd.DataFrame({'a': [1., 2.3, 4.4], 'b': [2.2, 3, np.nan]}, dtype='float32')
>>> df.sum(axis=1, min_count=1).dtype
dtype('float32')  # OK
>>> df.sum(axis=1, min_count=2).dtype
dtype('float64')  # not OK
>>> df.sum(axis=1, skipna=False).dtype
dtype('float32')  # OK

Issue Description

When using min_count, the dtype of the result depends on whether the result contains a NaN or not.

Expected Behavior

The resulting dtype should be the same as the dtype of the original DataFrame, also when the result contains NaNs.

Installed Versions

INSTALLED VERSIONS

commit : 4bfe3d0
python : 3.10.2.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19043
machine : AMD64
processor : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 1.4.2
numpy : 1.22.3
pytz : 2022.1
dateutil : 2.8.2
pip : 22.0.4
setuptools : 58.1.0
Cython : None
pytest : 7.0.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.8.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.1
IPython : 8.1.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.4
brotli : None
fastparquet : None
fsspec : 2022.02.0
gcsfs : None
markupsafe : 2.1.0
matplotlib : 3.5.1
numba : None
numexpr : 2.8.1
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 7.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.8.0
snappy : None
sqlalchemy : 1.4.32
tables : None
tabulate : 0.8.9
xarray : 2022.3.0
xlrd : None
xlwt : None
zstandard : None
@kdebrab kdebrab added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels May 5, 2022
@Anupam-USP
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I want to take this issue. Is there any reference to take help?

@simonjayhawkins
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thanks @Anupam-USP

things look good upto the _maybe_null_out call from nansum in pandas/core/nanops.py

pandas/pandas/core/nanops.py

Lines 626 to 629 in f7dda79

the_sum = values.sum(axis, dtype=dtype_sum)
the_sum = _maybe_null_out(the_sum, axis, mask, values.shape, min_count=min_count)
return the_sum

where the code sample for the failing case gets cast to float64 here

pandas/pandas/core/nanops.py

Line 1475 in f7dda79

result = result.astype("f8")

@simonjayhawkins simonjayhawkins added Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Reduction Operations sum, mean, min, max, etc. and removed Needs Triage Issue that has not been reviewed by a pandas team member labels May 18, 2022
@simonjayhawkins simonjayhawkins added this to the Contributions Welcome milestone May 18, 2022
@simonjayhawkins simonjayhawkins added the Dtype Conversions Unexpected or buggy dtype conversions label May 18, 2022
@weikhor weikhor mentioned this issue May 22, 2022
Merged
4 tasks
@jreback jreback modified the milestones: Contributions Welcome, 1.5 May 29, 2022
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Bug Fix: pd.DataFrame.sum with min_count changes dtype if result contains NaNs weikhor/pandas
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@jreback @kdebrab @simonjayhawkins @Anupam-USP