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https://issues.apache.org/jira/browse/ARROW-5713?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney updated ARROW-5713:
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Summary: [Python] fancy indexing on pa.array (was: fancy indexing on
pa.array)
> [Python] fancy indexing on pa.array
> -----------------------------------
>
> Key: ARROW-5713
> URL: https://issues.apache.org/jira/browse/ARROW-5713
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
> Reporter: Artem KOZHEVNIKOV
> Priority: Major
>
> In numpy one can do :
> {code:java}
> In [2]: import numpy as np
>
>
> In [3]: a = np.array(['a', 'bb', 'ccc', 'dddd'], dtype="O")
>
>
> In [4]: indices = np.array([0, -1, 2, 2, 0, 3])
>
>
> In [5]: a[indices]
>
>
> Out[5]: array(['a', 'dddd', 'ccc', 'ccc', 'a', 'dddd'], dtype=object)
> {code}
> It would be nice to have a similar feature in pyarrow.
> Currently, pa.arrow __getitem__ supports only a slice or a single element as
> an argument.
> Of course, using that we've some workarounds, like below
> {code:java}
> In [6]: import pyarrow as pa
>
>
> In [7]: a = pa.array(['a', 'bb', 'ccc', 'dddd'])
>
>
> In [8]: pa.array(a.to_pandas()[indices]) # if len(indices) is high
>
>
> Out[8]:
> <pyarrow.lib.StringArray object at 0x91bd845e8>
> [
> "a",
> "dddd",
> "ccc",
> "ccc",
> "a",
> "dddd"
> ]
> In [9]: pa.array([a[i].as_py() for i in indices]) # if len(indices) is low
>
> Out[9]:
> <pyarrow.lib.StringArray object at 0x91bc14868>
> [
> "a",
> "dddd",
> "ccc",
> "ccc",
> "a",
> "dddd"
> ]
> {code}
> both are not memory&cpu efficient.
>
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