BUG: to_stata() creates corrupt output file when value_labels is specified and version is 118 or greater · Issue #46750 · pandas-dev/pandas (original) (raw)

Pandas version checks

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• 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 pandas as pd df = pd.DataFrame( { "fully_labelled": [1, 2, 3, 3, 1], } )

value_labels = { "fully_labelled": {1: "one", 2: "two", 3: "three"}, }

df.to_stata("test.dta", value_labels = value_labels, version = 118)

Issue Description

When attempting to open the file created by the above code in Stata 17 MP the following error message is returned:

.dta file corrupt
    The file unexpectedly ended before it should have.
r(612);

This also occurs if version is set to 119.

I believe that this is because the space allocated for the label name is 33 bytes instead of the required 129, as the encoding is set to latin-1 by default and has not been changed to utf-8 based on the specified version.

If I change the line:

svl = StataNonCatValueLabel(colname, labels)

to:

svl = StataNonCatValueLabel(colname, labels, self._encoding)

in the function _prepare_non_cat_value_labels() in /pandas/io/stata.py

and run the example again then the file created appears to open successfully with the value labels intact.

Expected Behavior

No error message is returned, the data is loaded into Stata and the value labels are correctly applied.

Installed Versions

INSTALLED VERSIONS

commit : 4bfe3d0
python : 3.10.4.final.0
python-bits : 64
OS : Windows
OS-release : 2012ServerR2
Version : 6.3.9600
machine : AMD64
processor : Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252

pandas : 1.4.2
numpy : 1.21.5
pytz : 2022.1
dateutil : 2.8.2
pip : 22.0.4
setuptools : 62.1.0
Cython : 0.29.28
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.8.0
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.1
IPython : 8.2.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : 2.1.1
matplotlib : 3.5.1
numba : 0.55.1
numexpr : 2.8.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.8.0
snappy : None
sqlalchemy : 1.4.35
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None