[jira] [Updated] (ARROW-7617) [Python] parquet.write_to_dataset creates empty partitions for non-observed dictionary items (categories)

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-7617?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joris Van den Bossche updated ARROW-7617:
-----------------------------------------
    Labels: dataset dataset-parquet-write parquet  (was: dataset parquet)

> [Python] parquet.write_to_dataset creates empty partitions for non-observed dictionary items (categories)
> ---------------------------------------------------------------------------------------------------------
>
>                 Key: ARROW-7617
>                 URL: https://issues.apache.org/jira/browse/ARROW-7617
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.15.1
>            Reporter: Vladimir
>            Assignee: Andrew Wieteska
>            Priority: Major
>              Labels: dataset, dataset-parquet-write, parquet
>
> Hello,
> it looks like, views with selection along categorical column are not properly respected.
> For the following dummy dataframe:
>  
> {code:java}
> d = pd.date_range('1990-01-01', freq='D', periods=10000)
> vals = pd.np.random.randn(len(d), 4)
> x = pd.DataFrame(vals, index=d, columns=['A', 'B', 'C', 'D'])
> x['Year'] = x.index.year
> {code}
> The slice by Year is saved to partitioned parquet properly:
> {code:java}
> table = pa.Table.from_pandas(x[x.Year==1990], preserve_index=False)
> pq.write_to_dataset(table, root_path='test_a.parquet', partition_cols=['Year']){code}
> However, if we convert Year to pandas.Categorical - it will save the whole original dataframe, not only slice of Year=1990:
> {code:java}
> x['Year'] = x['Year'].astype('category')
> table = pa.Table.from_pandas(x[x.Year==1990], preserve_index=False)
> pq.write_to_dataset(table, root_path='test_b.parquet', partition_cols=['Year'])
> {code}
>  
>  



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