pandas.api.interchange.from_dataframe

pandas.api.interchange.from_dataframe(df, allow_copy=True)[source]

Build a pd.DataFrame from any DataFrame supporting 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. From pandas 2.3 onwards, from_dataframe uses the PyCapsule Interface, only falling back to the interchange protocol if that fails.

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:

df:DataFrameXchg

Object supporting the interchange protocol, i.e. __dataframe__ method.

allow_copy:bool, default: True

Whether to allow copying the memory to perform the conversion (if false then zero-copy approach is requested).

Returns:

pd.DataFrame

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.