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Posted to issues@arrow.apache.org by "Wes McKinney (JIRA)" <ji...@apache.org> on 2019/06/24 23:16:00 UTC

[jira] [Commented] (ARROW-5713) [Python] fancy indexing on pa.array

    [ https://issues.apache.org/jira/browse/ARROW-5713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16871872#comment-16871872 ] 

Wes McKinney commented on ARROW-5713:
-------------------------------------

We intend to support this with the {{Array.take}} function. I don't think I want to overload {{__getitem__}} 

> [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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