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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def load_febrl4(return_links=False):
 """Load the FEBRL 4 datasets. The Freely Extensible Biomedical Record Linkage (Febrl) package is distributed with a dataset generator and four datasets generated with the generator. This function returns the fourth Febrl dataset as a :class:`pandas.DataFrame`. *"Generated as one data set with 10000 records (5000 originals and 5000 duplicates, with one duplicate per original), the originals have been split from the duplicates, into dataset4a.csv (containing the 5000 original records) and dataset4b.csv (containing the 5000 duplicate records) These two data sets can be used for testing linkage procedures."* Parameters return_links: bool When True, the function returns also the true links. Returns ------- (pandas.DataFrame, pandas.DataFrame) A :class:`pandas.DataFrame` with Febrl dataset4a.csv and a pandas dataframe with Febrl dataset4b.csv. When return_links is True, the function returns also the true links. """


    df_a = _febrl_load_data('dataset4a.csv')
    df_b = _febrl_load_data('dataset4b.csv')

    if return_links:
        links = pandas.MultiIndex.from_arrays([
            ["rec-{}-org".format(i) for i in range(0, 5000)],
            ["rec-{}-dup-0".format(i) for i in range(0, 5000)]]
        )
        return df_a, df_b, links
    else:
        return df_a, df_b