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Posted to jira@arrow.apache.org by "Wes McKinney (Jira)" <ji...@apache.org> on 2020/06/16 15:09:00 UTC

[jira] [Updated] (ARROW-9136) [Python] pandas index information gets lost when partition_cols are used

     [ https://issues.apache.org/jira/browse/ARROW-9136?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wes McKinney updated ARROW-9136:
--------------------------------
    Summary: [Python] pandas index information gets lost when partition_cols are used  (was: pandas index information gets lost when partition_cols are used)

> [Python] pandas index information gets lost when partition_cols are used
> ------------------------------------------------------------------------
>
>                 Key: ARROW-9136
>                 URL: https://issues.apache.org/jira/browse/ARROW-9136
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.17.1
>            Reporter: Hans Pirnay
>            Priority: Major
>
> I originally reported this as a pandas github issue [https://github.com/pandas-dev/pandas/issues/34790]
>  
> To reproduce:
> {code:python}
> df = pd.DataFrame({'Data': [1, 2], 'partition': [1, 2]}, index=['2000-01-01', '2010-01-02'])
> data_path_with_partitions = 'with_partitions.parquet'
> df.to_parquet(data_path_with_partitions, partition_cols=['partition'])
> df_read_with_partitions = pd.read_parquet(data_path_with_partitions)
> pd.testing.assert_frame_equal(df, df_read_with_partitions)  # <-- this fails because the index has been turned into an extra column __index_level_0
> {code}
> As far as I can tell the issue is in the pandas integration of {{pyarrow.parquet}}, in particular that the {{subtable.schema.metadata[b'pandas']}} of the {{subtable}} generated in {{pyarrow/parquet.py:1725}} no longer contains the index column info passed in via {{subschema.metadata[b'pandas']}}. This overwriting happens in {{pyarrow/pandas_compat.py:595}}. 
>  
> I tried working around this by creating a *{{_common_schema}} file, but since the metadata of the individual datasets all have (incorrect) {{b'pandas'}} keys, these are prioritized.



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