pandas.DataFrame.__dataframe__

DataFrame.__dataframe__(nan_as_null=False, allow_copy=True)

Return the dataframe interchange object implementing the interchange protocol.

Note

For new development, we highly recommend using the Arrow C Data Interface alongside the Arrow PyCapsule Interface instead of the interchange protocol

Warning

Due to severe implementation issues, we recommend only considering using the interchange protocol in the following cases:

• converting to pandas: for pandas >= 2.0.3

• converting from pandas: for pandas >= 3.0.0

Parameters:

nan_as_nullbool, default False

nan_as_null is DEPRECATED and has no effect. Please avoid using it; it will be removed in a future release.

allow_copybool, default True

Whether to allow memory copying when exporting. If set to False it would cause non-zero-copy exports to fail.

Returns:

DataFrame interchange object

The object which consuming library can use to ingress the dataframe.

See also

DataFrame.from_records

Constructor from tuples, also record arrays.

DataFrame.from_dict

From dicts of Series, arrays, or dicts.

Notes

Details on the interchange protocol: https://data-apis.org/dataframe-protocol/latest/index.html

Examples

>>> df_not_necessarily_pandas = pd.DataFrame({"A": [1, 2], "B": [3, 4]})
>>> interchange_object = df_not_necessarily_pandas.__dataframe__()
>>> interchange_object.column_names()
Index(['A', 'B'], dtype='object')
>>> df_pandas = pd.api.interchange.from_dataframe(
...     interchange_object.select_columns_by_name(["A"])
... )
>>> df_pandas
     A
0    1
1    2

These methods (column_names, select_columns_by_name) should work for any dataframe library which implements the interchange protocol.