Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
########### PowerShell ############
import pandas as pd
df = pd.DataFrame({'A': ['\x00']})
df.to_csv('null_byte.csv', index=False)
# Error: need to escape, but no escapechar set
import pandas as pd
df = pd.DataFrame({'A': ['\x00']})
df.to_csv('null_byte.csv', index=False, escapechar='\\')
# Works, BUT escapechar appears to be redundant, because there is no escapechar in the file on disk!
$ xxd null_byte.csv # from WSL, because no xxd in PowerShell
00000000: 410d 0a00 0d0a A.....
########### Ubuntu/Bash ############
import pandas as pd
df = pd.DataFrame({'A': ['\x00']})
df.to_csv('null_byte.csv', index=False)
# WORKS, but output has different format:
$ xxd null_byte.csv
00000000: 410a 2200 220a A.".".Issue Description
NOTE: I'm running this in PowerShell, but using xxd from Windows Subsystem for Linux.
If a dataframe contains a null byte \x00 as a value, to_csv requires escapechar to be set when run from PowerShell, but not when run from Ubuntu/Bash. However, the escapechar is not actually used, and does not appear in the output file.
Expected Behavior
I expect that if escapechar is not used, I shouldn't need to use escapechar='\\'.
I also expect that the flags for to_csv should be the same for both PowerShell and Ubuntu/Bash.
i.e. I expect that the following should just work in both PowerShell and Bash, without needing to specify escapechar:
import pandas as pd
df = pd.DataFrame({'A': ['\x00']})
df.to_csv('null_byte.csv', index=False)Installed Versions
Pandas in Powershell:
INSTALLED VERSIONS
commit : e8093ba
python : 3.10.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22000
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Australia.1252
pandas : 1.4.3
numpy : 1.23.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 58.1.0
pip : 22.0.4
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : 0.8.1
fsspec : 2022.5.0
gcsfs : None
markupsafe : 2.1.1
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 6.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.39
tables : None
tabulate : 0.8.10
xarray : None
xlrd : None
xlwt : None
zstandard : None
Pandas in Ubuntu/Bash
INSTALLED VERSIONS
commit : e8093ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.3
numpy : 1.23.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 63.2.0
pip : 22.2
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 : 8.4.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : 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