[Python] from_pandas gives incorrect results when converting floating point to bool

[asfimport]

When converting Pandas data that contains floating point values to boolean, incorrect results are given

In [2]: import pyarrow as pa
 ...: import pandas as pd
 ...: a = [0.0, 1.0, 2.0, None, float('NaN')]
 ...: 

In [3]: s = pd.Series(a)

In [4]: pa.Array.from_pandas(s, type=pa.bool_())
Out[4]: 
<pyarrow.lib.BooleanArray object at 0x7f1bfd099e68>
[
 False,
 False,
 False,
 False,
 False
]

Expected output should be True when value != 0

This originated from SPARK-25461

Reporter: Bryan Cutler / @BryanCutler
Assignee: Bryan Cutler / @BryanCutler

Related issues:

• PySpark Pandas UDF outputs incorrect results when input columns contain None (relates to)

PRs and other links:

• GitHub Pull Request #2698

_{Note: This issue was originally created as ARROW-3428. Please see the migration documentation for further details.}

[asfimport]

Wes McKinney / @wesm:
Issue resolved by pull request 2698
#2698