[Python] DataFrame interchange: from_dataframe rejects every pandas float16 column #51696

Describe the bug, including details regarding any error messages, version, and platform.

pa.interchange.from_dataframe raises NotImplementedError for a pandas float16 column, with or without a NaN in it. pandas reports NaN as the null kind for every float column, and validity_buffer_nan_sentinel in python/pyarrow/interchange/from_dataframe.py:549 refuses float16 with that null kind. The comment there says pyarrow.compute.is_nan has no float16 kernel. That kernel arrived in #46866 (GH-45083), so the guard is stale.

$ python -c 'import numpy as np, pandas as pd, pyarrow as pa
from pyarrow.interchange import from_dataframe
print(from_dataframe(pd.DataFrame({"h": np.array([1.5], dtype="<f2")})))'
NotImplementedError: (<DtypeKind.FLOAT: 2>, 16, 'e', '=') with 1 is not yet supported.
# pyarrow 26.0.0.dev350 nightly wheel, pandas 3.2.0.dev0, CPython 3.12, Linux x86_64

With the float16 branch removed, so the NaN mask goes through pc.is_nan like float32 and float64:

$ python -m pytest -q pyarrow/tests/interchange/
# main e85e181
3045 passed, 2 skipped
# branch removed, test_pandas_to_pyarrow_float16_with_missing changed to expect [0, None, 2] as float16
3045 passed, 2 skipped
# that test change alone, from_dataframe.py at main
1 failed, 3044 passed, 2 skipped

The test test_pandas_to_pyarrow_float16_with_missing pins the old NotImplementedError, so it changes with the fix.

Component(s)

Python

I saw #49629. Until the protocol is removed, pa.table(df) imports the same column:

$ python -c 'import numpy as np, pandas as pd, pyarrow as pa
print(pa.table(pd.DataFrame({"h": np.array([1.5, np.nan], dtype="<f2")})))'
pyarrow.Table
h: halffloat
----
h: [[1.5,null]]
# pyarrow 26.0.0.dev350 nightly wheel, pandas 3.2.0.dev0

I have the patch, 14 lines added and 20 removed across those two files. Is it worth opening against this issue, or would you rather close this against #49629?