[jira] [Assigned] (ARROW-2646) [Python] Pandas roundtrip for date objects

2018-09-10 Thread Krisztian Szucs (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-2646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Krisztian Szucs reassigned ARROW-2646:
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Assignee: Krisztian Szucs  (was: Uwe L. Korn)

> [Python] Pandas roundtrip for date objects
> --
>
> Key: ARROW-2646
> URL: https://issues.apache.org/jira/browse/ARROW-2646
> Project: Apache Arrow
>  Issue Type: Bug
>  Components: Python
>Affects Versions: 0.9.0
>Reporter: Florian Jetter
>Assignee: Krisztian Szucs
>Priority: Minor
>  Labels: pull-request-available
> Fix For: 0.11.0
>
>  Time Spent: 20m
>  Remaining Estimate: 0h
>
> Arrow currently casts date objects to nanosecond precision datetime objects. 
> I'd like to have a way to preserve the type during a roundtrip
> {code}
> >>> import pandas as pd
> >>> import pyarrow as pa
> >>> import datetime
> >>> pa.date32().to_pandas_dtype()
> dtype(' >>> df = pd.DataFrame({'date': [datetime.date(2018, 1, 1)]})
> >>> df.dtypes
> date object
> dtype: object
> >>> df_rountrip = pa.Table.from_pandas(df).to_pandas()
> >>> df_rountrip.dtypes
> datedatetime64[ns]
> dtype: object
> {code}
> I'd expect something like this to work:
> {code}
> >>> import pandas.testing as pdt
> >>> df_rountrip = pa.Table.from_pandas(df).to_pandas(date_as_object=True)
> >>> pdt.assert_frame_equal(df_rountrip, df)
> {code}



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[jira] [Assigned] (ARROW-2646) [Python] Pandas roundtrip for date objects

2018-08-22 Thread Uwe L. Korn (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-2646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Uwe L. Korn reassigned ARROW-2646:
--

Assignee: Uwe L. Korn

> [Python] Pandas roundtrip for date objects
> --
>
> Key: ARROW-2646
> URL: https://issues.apache.org/jira/browse/ARROW-2646
> Project: Apache Arrow
>  Issue Type: Bug
>  Components: Python
>Affects Versions: 0.9.0
>Reporter: Florian Jetter
>Assignee: Uwe L. Korn
>Priority: Minor
> Fix For: 0.11.0
>
>
> Arrow currently casts date objects to nanosecond precision datetime objects. 
> I'd like to have a way to preserve the type during a roundtrip
> {code}
> >>> import pandas as pd
> >>> import pyarrow as pa
> >>> import datetime
> >>> pa.date32().to_pandas_dtype()
> dtype(' >>> df = pd.DataFrame({'date': [datetime.date(2018, 1, 1)]})
> >>> df.dtypes
> date object
> dtype: object
> >>> df_rountrip = pa.Table.from_pandas(df).to_pandas()
> >>> df_rountrip.dtypes
> datedatetime64[ns]
> dtype: object
> {code}
> I'd expect something like this to work:
> {code}
> >>> import pandas.testing as pdt
> >>> df_rountrip = pa.Table.from_pandas(df).to_pandas(date_as_object=True)
> >>> pdt.assert_frame_equal(df_rountrip, df)
> {code}



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