Repository: pandas-dev/pandas
File: pandas/core/frame.py (Python)

Code before:
        Write a DataFrame to an Apache Iceberg table.

        .. versionadded:: 3.0.0

        .. warning::

           to_iceberg is experimental and may change without warning.

        Parameters
        ----------
        table_identifier : str
            Table identifier.
        catalog_name : str, optional
            The name of the catalog.
        catalog_properties : dict of {str: str}, optional
            The properties that are used next to the catalog configuration.
        location : str, optional
            Location for the table.
        append : bool, default False
            If ``True``, append data to the table, instead of replacing the content.
        snapshot_properties : dict of {str: str}, optional
            Custom properties to be added to the snapshot summary
        engine : str, optional
            The engine to use. Engines can be installed via third-party packages. For an
            updated list of existing pandas I/O engines check the I/O engines section of
            our Ecosystem page.

        See Also
        --------
        read_iceberg : Read an Apache Iceberg table.
        DataFrame.to_parquet : Write a DataFrame in Parquet format.

        Examples
        --------
        >>> df = pd.DataFrame(data={"col1": [1, 2], "col2": [4, 3]})
        >>> df.to_iceberg("my_table", catalog_name="my_catalog")  # doctest: +SKIP
        """
        from pandas.io.iceberg import to_iceberg

        to_iceberg(
            self,
            table_identifier,
            catalog_name,
            catalog_properties=catalog_properties,
            location=location,
            append=append,
            snapshot_properties=snapshot_properties,
        )

    # ----------------------------------------------------------------------
    @doc(INFO_DOCSTRING, **frame_sub_kwargs)

Review comment (suggestion):
```suggestion
            the pandas Ecosystem page.
```

Code after:
        Write a DataFrame to an Apache Iceberg table.

        .. versionadded:: 3.0.0

        .. warning::

           to_iceberg is experimental and may change without warning.

        Parameters
        ----------
        table_identifier : str
            Table identifier.
        catalog_name : str, optional
            The name of the catalog.
        catalog_properties : dict of {str: str}, optional
            The properties that are used next to the catalog configuration.
        location : str, optional
            Location for the table.
        append : bool, default False
            If ``True``, append data to the table, instead of replacing the content.
        snapshot_properties : dict of {str: str}, optional
            Custom properties to be added to the snapshot summary
        engine : str, optional
            The engine to use. Engines can be installed via third-party packages. For an
            updated list of existing pandas I/O engines check the I/O engines section of
            the pandas Ecosystem page.

        See Also
        --------
        read_iceberg : Read an Apache Iceberg table.
        DataFrame.to_parquet : Write a DataFrame in Parquet format.

        Examples
        --------
        >>> df = pd.DataFrame(data={"col1": [1, 2], "col2": [4, 3]})
        >>> df.to_iceberg("my_table", catalog_name="my_catalog")  # doctest: +SKIP
        """
        from pandas.io.iceberg import to_iceberg

        to_iceberg(
            self,
            table_identifier,
            catalog_name,
            catalog_properties=catalog_properties,
            location=location,
            append=append,
            snapshot_properties=snapshot_properties,
        )

    # ----------------------------------------------------------------------
    @doc(INFO_DOCSTRING, **frame_sub_kwargs)