Wainberg opened a new issue, #40910:
URL: https://github.com/apache/arrow/issues/40910
### Describe the bug, including details regarding any error messages,
version, and platform.
When you mix `np.float32` or `np.float64` scalars and integers, the result
is `DoubleArray`:
```python
>>> pa.array([np.float32(0.5), 1])
<pyarrow.lib.DoubleArray object at 0x7fabb2f7c0a0>
[
0.5,
1
]
>>> pa.array([np.float64(0.5), 1])
<pyarrow.lib.DoubleArray object at 0x7fabb2f7c220>
[
0.5,
1
]
```
But when you mix `np.float16` or `np.float128` scalars and integers, the
result is `Int64Array`, and the floats are truncated to integers:
```python
>>> pa.array([np.float16(0.5), 1])
<pyarrow.lib.Int64Array object at 0x7fabb2f7c220>
[
0,
1
]
>>> pa.array([np.float128(0.5), 1])
<pyarrow.lib.Int64Array object at 0x7fabb2f7c0a0>
[
0,
1
]
```
### Component(s)
Python
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