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BUG: regression: pandas.read_stata(filename, iterator=True) raises ValueError #37280

@remram44

Description

@remram44
  • I have checked that this issue has not already been reported.

  • 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.


Code Sample, a copy-pastable example

>>> import pandas >>> # for example https://gitlab.com/ViDA-NYU/datamart/datamart/-/blob/master/tests/data/stata118.dta >>> iterator = pandas.read_stata(stata_file_name, iterator=True) >>> list(iterator) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "site-packages/pandas/io/stata.py", line 1523, in __next__ raise ValueError( ValueError: chunksize must be set to a positive integer to use as an iterator.

Problem description

read_stata(filename, iterator=True) no longer works in pandas 1.1.3. It worked in pandas 1.0.5.

Expected Output

DataFrame is loaded correctly

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : db08276bc116c438d3fdee492026f8223584c477 python : 3.8.5.final.0 python-bits : 64 OS : Linux OS-release : 5.4.0-51-generic Version : #56-Ubuntu SMP Mon Oct 5 14:28:49 UTC 2020 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.1.3 numpy : 1.19.2 pytz : 2020.1 dateutil : 2.8.1 pip : 20.0.2 setuptools : 44.0.0 Cython : None pytest : None hypothesis : None sphinx : 3.2.1 blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.11.2 IPython : 7.14.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : 0.8.4 fastparquet : None gcsfs : 0.7.1 matplotlib : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pytables : None pyxlsb : None s3fs : 0.4.2 scipy : 1.5.3 sqlalchemy : None tables : None tabulate : None xarray : None xlrd : 1.2.0 xlwt : None numba : None 

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    BugIO Stataread_stata, to_stataRegressionFunctionality that used to work in a prior pandas version

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