honno opened a new issue, #35535:
URL: https://github.com/apache/arrow/issues/35535
### Describe the bug, including details regarding any error messages,
version, and platform.
First of, this might not be a problem—let me know if that's the case! Hard
for me to wrap my head around the consequences of Arrow's NA model with
interchanging :sweat_smile:
So, if one were to interchange a `pandas.DataFrame` containing NaNs to a
`pyarrow.Table`, one gets nulls in place of NaNs.
```python
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame({"foo": pd.Series([float("nan")], dtype=np.float64)})
>>> from pyarrow.interchange import from_dataframe
>>> from_dataframe(df)
pyarrow.Table
foo: double
----
foo: [[null] # expect NaN?
```
We get the same with `modin`, which also adopts the interchange protocol.
```python
>>> import modin
>>> import ray
>>> ray.init(local_mode=True)
>>> from modin.config import Engine
>>> Engine.put("ray")
>>> from modin import pandas as mpd
>>> df = mpd.DataFrame({"foo": mpd.Series([float("nan")], dtype=np.float64)})
>>> from_dataframe(df)
pyarrow.Table
foo: double
----
foo: [[null]]
```
I see interchanging another `pa.Table` with NaNs works fine, asummedly
because `from_dataframe()` short-circuits when it gets a
`pa.Table`/`pa.RecordBatch`.
```python
>>> table = pa.Table.from_pydict({"foo": pa.array([float("nan")],
type=pa.float64())})
>>> from_dataframe(table)
pyarrow.Table
foo: double
----
foo: [[nan]]
```
Using the arrow nightly from https://pypi.fury.io/arrow-nightlies/
cc @AlenkaF
### Component(s)
Python
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