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https://issues.apache.org/jira/browse/ARROW-16081?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17515280#comment-17515280
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David Li commented on ARROW-16081:
----------------------------------
NumPy's bool [is a byte|https://numpy.org/devdocs/user/basics.types.html] while
Arrow's bool [is a
bit|https://arrow.apache.org/docs/format/Columnar.html#fixed-size-primitive-layout].
Converting it via an array instead of a buffer will work:
{noformat}
>>> import pyarrow as pa
>>> import numpy as np
>>> data = np.array([True, False, True, False], dtype=bool)
>>> arr = pa.array(data)
>>> arr.to_numpy(zero_copy_only=False)
array([ True, False, True, False])
>>> data
array([ True, False, True, False])
{noformat}
> Incorrect results when reading a buffer of boolean values
> ---------------------------------------------------------
>
> Key: ARROW-16081
> URL: https://issues.apache.org/jira/browse/ARROW-16081
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 7.0.0
> Environment: Ubuntu 20.04, Python 3.8.10, pyarrow==7.0.0
> Reporter: Jonathan Kenyon
> Priority: Major
>
> The following reproducer demonstrates that a buffer of boolean values is not
> correctly recovered when using pyarrow.
> {code:python}
> import pyarrow.parquet as pq
> import pyarrow as pa
> import numpy as np
> if __name__ == "__main__":
> data = np.array([True, False, True, False], dtype=bool)
> length = len(data)
> buf = pa.py_buffer(data)
> array = pa.Array.from_buffers(pa.bool_(), length, [None, buf])
> np.testing.assert_array_equal(data, array.to_numpy(zero_copy_only=False))
> {code}
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