def get_relevance(tinfo_df, l=.6):
    """Calculate Relevances with a given lambda value.
    
    Parameters
    ----------
    tinfo: pandas.DataFrame
        `pyLDAvis.gensim.prepare`.to_dict()['tinfo'] containing
        ['Category', 'Freq', 'Term', 'Total', 'loglift', 'logprob']

    l: float
        lambda_ratio between {0-1}. default is .6 (recommended from its paper)

    """

    relevance = l * tinfo_df['logprob'] + (1 - l) * tinfo_df['loglift']

    return relevance