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https://issues.apache.org/jira/browse/ARROW-2593?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Uwe L. Korn updated ARROW-2593:
-------------------------------
Fix Version/s: 0.10.0
> [Python] TypeError: data type "mixed-integer" not understood
> ------------------------------------------------------------
>
> Key: ARROW-2593
> URL: https://issues.apache.org/jira/browse/ARROW-2593
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.9.0
> Reporter: Dima Ryazanov
> Priority: Major
> Fix For: 0.10.0
>
>
> Pyarrow 0.9 raises an exception when converting some tables to pandas
> dataframes. Earlier versions work fine. Repro steps:
> {{In [1]: import pandas as pd}}
> {{In [2]: import pyarrow as pa}}
> {{In [3]: df = pd.DataFrame(\{'foo': [], 123: []})}}
> {{In [4]: table = pa.Table.from_pandas(df)}}
> {{In [5]: table.to_pandas()}}
> {{---------------------------------------------------------------------------}}
> {{KeyError Traceback (most recent call
> last)}}
> {{~/envs/cli3/lib/python3.6/site-packages/pyarrow/pandas_compat.py in
> _pandas_type_to_numpy_type(pandas_type)}}
> {{ 666 try:}}
> {{--> 667 return _pandas_logical_type_map[pandas_type]}}
> {{ 668 except KeyError:}}
> {{KeyError: 'mixed-integer'}}
> (I ended up with a dataframe with mixed string/integer columns by using
> pd.read_excel(..., skiprows=[0]) - which skipped the header, and treated the
> first line of data as column names.)
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