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GH-49628: [Python][Interchange protocol] Suppress warnings for pandas 4.0.0 and update docs #49630

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Merged
raulcd merged 6 commits into from
Apr 7, 2026
Merged

GH-49628: [Python][Interchange protocol] Suppress warnings for pandas 4.0.0 and update docs #49630

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d849c14
Add filterwarnings
AlenkaF Apr 1, 2026
3a1ec92
Remove pandas example from the docs
AlenkaF Apr 1, 2026
c8d1bc0
Remove Pandas4Warning
AlenkaF Apr 1, 2026
8f1e865
Remove example from from_dataframe docstrings
AlenkaF Apr 1, 2026
f6c48c9
Set pytestmark at the top
AlenkaF Apr 2, 2026
3abf63f
Add a note
AlenkaF Apr 2, 2026
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27 changes: 1 addition & 26 deletions docs/source/python/interchange_protocol.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -61,34 +61,9 @@ from any dataframe object that implements the
``__dataframe__()`` method via the dataframe interchange
protocol.

We can for example take a pandas dataframe and construct a
We can for example take a polars dataframe and construct a
Comment thread
AlenkaF marked this conversation as resolved.
PyArrow table with the use of the interchange protocol:

.. code-block:: python

>>> import pyarrow
>>> from pyarrow.interchange import from_dataframe

>>> import pandas as pd
>>> df = pd.DataFrame({
... "n_attendees": [100, 10, 1],
... "country": ["Italy", "Spain", "Slovenia"],
... })
>>> df
n_attendees country
0 100 Italy
1 10 Spain
2 1 Slovenia
>>> from_dataframe(df)
pyarrow.Table
n_attendees: int64
country: large_string
----
n_attendees: [[100,10,1]]
country: [["Italy","Spain","Slovenia"]]

We can do the same with a polars dataframe:

.. code-block:: python

>>> import polars as pl # doctest: +SKIP
Expand Down
25 changes: 0 additions & 25 deletions python/pyarrow/interchange/from_dataframe.py
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Expand Up @@ -76,31 +76,6 @@ def from_dataframe(df: DataFrameObject, allow_copy=True) -> pa.Table:
Returns
-------
pa.Table

Examples
--------
>>> import pyarrow
>>> from pyarrow.interchange import from_dataframe

Convert a pandas dataframe to a pyarrow table:

>>> import pandas as pd
>>> df = pd.DataFrame({
... "n_attendees": [100, 10, 1],
... "country": ["Italy", "Spain", "Slovenia"],
... })
>>> df
n_attendees country
0 100 Italy
1 10 Spain
2 1 Slovenia
>>> from_dataframe(df)
pyarrow.Table
n_attendees: int64
country: large_string
----
n_attendees: [[100,10,1]]
country: [["Italy","Spain","Slovenia"]]
"""
if isinstance(df, pa.Table):
return df
Expand Down
30 changes: 30 additions & 0 deletions python/pyarrow/tests/interchange/test_conversion.py
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Expand Up @@ -103,6 +103,9 @@ def test_offset_of_sliced_array():
# check_index=False, check_names=False)


@pytest.mark.filterwarnings(
Comment thread
AlenkaF marked this conversation as resolved.
Outdated
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
@pytest.mark.parametrize(
"uint", [pa.uint8(), pa.uint16(), pa.uint32()]
Expand Down Expand Up @@ -146,6 +149,9 @@ def test_pandas_roundtrip(uint, int, float, np_float_str):
assert table_protocol.column_names() == result_protocol.column_names()


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_pandas_roundtrip_string():
# See https://github.com/pandas-dev/pandas/issues/50554
Expand Down Expand Up @@ -175,6 +181,9 @@ def test_pandas_roundtrip_string():
assert table_protocol.column_names() == result_protocol.column_names()


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_pandas_roundtrip_large_string():
# See https://github.com/pandas-dev/pandas/issues/50554
Expand Down Expand Up @@ -212,6 +221,9 @@ def test_pandas_roundtrip_large_string():
pandas_from_dataframe(table)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_pandas_roundtrip_string_with_missing():
# See https://github.com/pandas-dev/pandas/issues/50554
Expand Down Expand Up @@ -244,6 +256,9 @@ def test_pandas_roundtrip_string_with_missing():
pandas_from_dataframe(table)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_pandas_roundtrip_categorical():
if Version(pd.__version__) < Version("2.0.2"):
Expand Down Expand Up @@ -292,6 +307,9 @@ def test_pandas_roundtrip_categorical():
assert isinstance(desc_cat_result["categories"]._col, pa.Array)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
@pytest.mark.parametrize("unit", ['s', 'ms', 'us', 'ns'])
def test_pandas_roundtrip_datetime(unit):
Expand Down Expand Up @@ -328,6 +346,9 @@ def test_pandas_roundtrip_datetime(unit):
assert expected_protocol.column_names() == result_protocol.column_names()


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
@pytest.mark.parametrize(
"np_float_str", ["float32", "float64"]
Expand All @@ -353,6 +374,9 @@ def test_pandas_to_pyarrow_with_missing(np_float_str):
assert result.equals(expected)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_pandas_to_pyarrow_float16_with_missing():
if Version(pd.__version__) < Version("1.5.0"):
Expand Down Expand Up @@ -476,6 +500,9 @@ def test_nan_as_null():
table.__dataframe__(nan_as_null=True)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_allow_copy_false():
if Version(pd.__version__) < Version("1.5.0"):
Expand All @@ -495,6 +522,9 @@ def test_allow_copy_false():
pi.from_dataframe(df, allow_copy=False)


@pytest.mark.filterwarnings(
"ignore:The Dataframe Interchange Protocol is deprecated."
)
@pytest.mark.pandas
def test_allow_copy_false_bool_categorical():
if Version(pd.__version__) < Version("1.5.0"):
Expand Down
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