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https://issues.apache.org/jira/browse/ARROW-2205?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Uwe L. Korn resolved ARROW-2205.
--------------------------------
Resolution: Fixed
Issue resolved by pull request 1650
[https://github.com/apache/arrow/pull/1650]
> [Python] Option for integer object nulls
> ----------------------------------------
>
> Key: ARROW-2205
> URL: https://issues.apache.org/jira/browse/ARROW-2205
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
> Affects Versions: 0.8.0
> Reporter: Albert Shieh
> Assignee: Albert Shieh
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.9.0
>
>
> I have a use case where the loss of precision in casting integers to floats
> matters, and pandas supports storing integers with nulls without loss of
> precision in object columns. However, a roundtrip through arrow will cast the
> object columns to float columns, even though the object columns are stored in
> arrow as integers with nulls.
> This is a minimal example demonstrating the behavior of a roundtrip:
> {code}
> import numpy as np
> import pandas as pd
> import pyarrow as pa
> df = pd.DataFrame({"a": np.array([None, 1], dtype=object)})
> df_pa = pa.Table.from_pandas(df).to_pandas()
> print(df)
> print(df_pa)
> {code}
> The output is:
> {code}
> a
> 0 None
> 1 1
> a
> 0 NaN
> 1 1.0
> {code}
> This seems to be the desired behavior, given test_int_object_nulls in
> test_convert_pandas.
> I think it would be useful to add an option in the to_pandas methods to allow
> integers with nulls to be returned as object columns. The option can default
> to false in order to preserve the current behavior.
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