[
https://issues.apache.org/jira/browse/ARROW-7782?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17031678#comment-17031678
]
Ludwik Bielczynski commented on ARROW-7782:
-------------------------------------------
Maybe I was not clear. The index is moved from the index to the columns. That's
the buggy behaviour I am describing. Version 0.9 before ARROW-2891 preserved
the index as an index between writting and reading tha dataframe.
Does it make sense?
> 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, read_table
> 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']
> )
> df_read = read_table(str(path / file_name))
> df_read.to_pandas()
> {code}
>
> The issue is rather important for pandas and dask users.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
