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Posted to issues@arrow.apache.org by "Artem KOZHEVNIKOV (JIRA)" <ji...@apache.org> on 2019/06/24 18:47:00 UTC
[jira] [Created] (ARROW-5713) fancy indexing on pa.array
Artem KOZHEVNIKOV created ARROW-5713:
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Summary: 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
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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