[jira] [Commented] (ARROW-7782) Losing index information when using write_to_dataset with partition_cols

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

    [ https://issues.apache.org/jira/browse/ARROW-7782?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17031673#comment-17031673 ] 

Joris Van den Bossche commented on ARROW-7782:
----------------------------------------------

This might be solved in master (will be released as 0.16 this week):

{code}
In [1]: from pathlib import Path 
   ...: import pandas as pd 
   ...: from pyarrow import Table 
   ...: from pyarrow.parquet import write_to_dataset 
   ...: path = Path('.') 
   ...: file_name = 'trial_pq.parquet' 
   ...: df = pd.DataFrame({"A": [1, 2, 3],  
   ...:  "B": ['a', 'a', 'b'] 
   ...:  },  
   ...:  index=pd.Index(['a', 'b', 'c'], name='idx')) 
   ...:  
   ...: table = Table.from_pandas(df) 
   ...: write_to_dataset(table, str(path / file_name), partition_cols=['B'], 
   ...:  partition_filename_cb=None, filesystem=None) 
   ...:                                                                                                                                                                                                            

In [2]: table                                                                                                                                                                                                      
Out[2]: 
pyarrow.Table
A: int64
B: string
idx: string
metadata
--------
{b'pandas': b'{"index_columns": ["idx"], "column_indexes": [{"name": null, "fi'
            b'eld_name": null, "pandas_type": "unicode", "numpy_type": "object'
            b'", "metadata": {"encoding": "UTF-8"}}], "columns": [{"name": "A"'
            b', "field_name": "A", "pandas_type": "int64", "numpy_type": "int6'
            b'4", "metadata": null}, {"name": "B", "field_name": "B", "pandas_'
            b'type": "unicode", "numpy_type": "object", "metadata": null}, {"n'
            b'ame": "idx", "field_name": "idx", "pandas_type": "unicode", "num'
            b'py_type": "object", "metadata": null}], "creator": {"library": "'
            b'pyarrow", "version": "0.15.1.dev736+g46d0b7f47"}, "pandas_versio'
            b'n": "1.1.0.dev0+369.ga62dbda20"}'}

In [3]: pd.read_parquet(file_name)                                                                                                                                                                                 
Out[3]: 
   A idx  B
0  1   a  a
1  2   b  a
2  3   c  b
{code}

which seem to preserve the "idx" index as a column?

> Losing index information when using write_to_dataset with partition_cols
> ------------------------------------------------------------------------
>
>                 Key: ARROW-7782
>                 URL: https://issues.apache.org/jira/browse/ARROW-7782
>             Project: Apache Arrow
>          Issue Type: Bug
>         Environment: pyarrow==0.15.1
>            Reporter: Ludwik Bielczynski
>            Priority: Major
>
> One cannot save the index when using {{pyarrow.parquet.write_to_dataset()}} with given partition_cols arguments. Here I have created a minimal example which shows the issue:
> {code:java}
>  
> from pathlib import Path
> import pandas as pd
> from pyarrow import Table
> from pyarrow.parquet import write_to_dataset
> path = Path('/home/user/trials')
> file_name = 'local_database.parquet'
> df = pd.DataFrame({"A": [1, 2, 3], "B": ['a', 'a', 'b']}, 
>                   index=pd.Index(['a', 'b', 'c'], 
>                   name='idx'))
> table = Table.from_pandas(df)
> write_to_dataset(table, 
>                  str(path / file_name), 
>                  partition_cols=['B']
>                 )
> {code}
>  
> The issue is rather important for pandas and dask users.



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