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BUG: Groupby then sum boolean column gives too large a sum #50347
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Needs Tests
Unit test(s) needed to prevent regressions
Upstream issue
Issue related to pandas dependency
Comments
this might be a numpy issue In [77]: a = np.array([True] * 32)
In [78]: b = (a == True)
In [79]: b.view('uint8')
Out[79]:
array([254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254,
254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254,
254, 254, 254, 254, 254, 254], dtype=uint8)
In [80]: np.__version__
Out[80]: '1.24.0' |
This works on main for me, so might need tests. We made quite a lot of changes on groupby algorithms to preserve dtypes better, so could be related to that |
I don't think this works on main In [3]: pd.__version__, np.__version__
Out[3]: ('2.0.0.dev0+971.gca3e0c875f', '1.24.0')
In [4]: n = 32
...: df = pd.DataFrame({'label': 1, 'a': [True] * n})
...: df['b'] = df['a'] == True
...: df.groupby('label').sum()
Out[4]:
a b
label
1 32 8128 |
Hm good point, did not use numpy 1.24.0 |
This is now fixed in numpy 1.24.1 |
5 tasks
take |
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Labels
Groupby
Needs Tests
Unit test(s) needed to prevent regressions
Upstream issue
Issue related to pandas dependency
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Reproducible Example
Issue Description
Summing a boolean column after a groupby gives an unreasonably large and incorrect sum.
This is the result from the above code:
1 8128 Name: bool_column_dupe, dtype: int64
The issue does not occur if I instead add an
astype(int)
:print(df.assign(bool_column_dupe(df.bool_column==True).astype(int)).groupby("label").bool_column_dupe.sum())
The issue does not occur if I don't use the
.assign
:print(df.groupby("label").bool_column.sum())
The issue does not occur with
n<32
.The issue only occurs with numpy v1.24.0.
It does not occur with numpy v1.23.5.
Expected Behavior
Expected to see:
1 32 Name: bool_column_dupe, dtype: int64
Installed Versions
INSTALLED VERSIONS
commit : 8dab54d
python : 3.9.13.final.0
python-bits : 64
OS : Darwin
OS-release : 22.1.0
Version : Darwin Kernel Version 22.1.0: Sun Oct 9 20:14:54 PDT 2022; root:xnu-8792.41.9~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_GB.UTF-8
pandas : 1.5.2
numpy : 1.24.0
pytz : 2022.7
dateutil : 2.8.2
setuptools : 60.2.0
pip : 21.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None
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