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https://issues.apache.org/jira/browse/ARROW-6325?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16913575#comment-16913575
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Joris Van den Bossche commented on ARROW-6325:
----------------------------------------------
A numpy only reproducer. Starting from a 2D array, slicing a row is fine, but
slicing a column gives the problems:
{code}
In [64]: a = np.ones((3, 2), dtype=bool)
In [65]: pa.array(a[0, :])
Out[65]:
<pyarrow.lib.BooleanArray object at 0x7fd093368d00>
[
true,
true
]
In [66]: pa.array(a[:, 0])
Out[66]:
<pyarrow.lib.BooleanArray object at 0x7fd093368bf8>
[
true,
false,
false
]
{code}
> [Python] wrong conversion of DataFrame with boolean values
> ----------------------------------------------------------
>
> Key: ARROW-6325
> URL: https://issues.apache.org/jira/browse/ARROW-6325
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.14.1
> Reporter: Joris Van den Bossche
> Priority: Major
> Fix For: 0.15.0
>
>
> From https://github.com/pandas-dev/pandas/issues/28090
> {code}
> In [19]: df = pd.DataFrame(np.ones((3, 2), dtype=bool), columns=['a', 'b'])
> In [20]: df
> Out[20]:
> a b
> 0 True True
> 1 True True
> 2 True True
> In [21]: table = pa.table(df)
> In [23]: table.column(0)
> Out[23]:
> <pyarrow.lib.ChunkedArray object at 0x7fd08a96e090>
> [
> [
> true,
> false,
> false,
> ]
> ]
> {code}
> The resulting table has False values while the original DataFrame had only
> true values.
> It seems this has to do with the fact that it are multiple columns, as with a
> single column it converts correctly.
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