def METHOD_NAME(data: pd.DataFrame) -> pd.DataFrame:
    """Prepare data before saving it to meadow.
    Parameters
    ----------
    data : pd.DataFrame
        Data.
    Returns
    -------
    df : pd.DataFrame
        Data ready to be stored as a table in meadow.
    """
    df = data.copy()
    # Select columns to keep.
    # Note:
    # * Ignore column "Year Code" (which is almost identical to "Year", and does not add information).
    # * Ignore column "Note" (which is included only in faostat_fa, faostat_fs, and faostat_sdgb datasets).
    # * Add "Recipient Country Code" and "Recipient Code", which are the names for "Area Code" and "Area", respectively,
    #   for dataset faostat_fa.
    columns_to_keep = [
        "Area Code",
        "Area",
        "Year",
        "Item Code",
        "Item",
        "Element Code",
        "Element",
        "Unit",
        "Value",
        "Flag",
        "Recipient Country Code",
        "Recipient Country",
    ]
    # Select only columns that are found in the dataframe.
    columns_to_keep = list(set(columns_to_keep) & set(df.columns))
    df = df[columns_to_keep]
    # Set index columns depending on what columns are available in the dataframe.
    # Note: "Recipient Country Code" appears only in faostat_fa, and seems to replace "Area Code".
    index_columns = list({"Area Code", "Recipient Country Code", "Year", "Item Code", "Element Code"} & set(df.columns))
    if df.duplicated(subset=index_columns).any():
        log.warning("Index has duplicated keys.")
    df = df.set_index(index_columns)
    return df