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BUG: dataframe concatenation segementation fault (core dump) #39144
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Please provide a reproducible example https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports |
@phofl Is there a way for me to pin down the bug on my side? It only happens to to files in two folder. I can't do the minimal bug report, because it has more than 1000 files. |
You could do a git bisect to narrow down when this was introduced IAlternatively it should be sufficientto use only these files? Maybe you could create the DataFrames casing the segfaults in code? |
@stokhos a good start would probably to check whether the segfault happens in the concat function or actually in the In case it's caused by |
Closing for now, but please do let us know if you have a reproducible example, as per:
|
I was able to reliably reproduce a segfault with a single row CSV on read_csv on pandas 1.2.0, however upgrading to 1.2.3 fixed it. |
@djherbis could you share that csv please? |
It's unfortunately got some private data in it, I'll try to narrow it down to single row, single column, and scrub the data so that it repros without private info. |
Looks like this may have been the same issue as #38753 (comment) which was fixed since using the float_precision="legacy" worked even on 1.2.0. |
Yeah I think it's that issue, narrowed it down to just this: echo "id" > crash.csv
echo "0E59181149492B9CCD27179CDB27EBEC" >> crash.csv import pandas as pd
pd.read_csv('crash.csv') Looks like pandas treats that string as an exponent number. |
Thanks @djherbis - I'll do a bisect later, we may need to add a test for this |
You can check the other bug I linked too, I believe they may have already reported and fixed this particular issue. |
This was fixed in #38789
so I think we can close - thanks anyway for the useful reproducer! |
[ X ] I have checked that this issue has not already been reported.
[ X ] 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
Problem description
A subgroup of my files can cause the above function to break. And it happens 100% with those files with pandas1.2.0, with 1.1.5 no problem.
[this should explain why the current behaviour is a problem and why the expected output is a better solution]
Expected Output
Output of
pd.show_versions()
[paste the output of
pd.show_versions()
here leaving a blank line after the details tag]pandas : 1.2.0
numpy : 1.19.5
pytz : 2020.5
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.1.3
Cython : 0.29.21
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: 0.9.0
bs4 : 4.9.3
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : 0.8.7
xarray : None
xlrd : None
xlwt : None
numba : None
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