Returns
        -------
        A pd.DataFrame consisting of unigram term counts of words occurring
         in the TermDocumentMatrix and their corresponding background corpus
         counts.  The dataframe has two columns, corpus and background.

        >>> corpus.get_unigram_corpus().get_term_and_background_counts()
                          corpus  background
        obama              702.0    565739.0
        romney             570.0    695398.0
        barack             248.0    227861.0
        ...

def get_term_and_background_counts(self):
        '''
        Returns
        -------
        A pd.DataFrame consisting of unigram term counts of words occurring
         in the TermDocumentMatrix and their corresponding background corpus
         counts.  The dataframe has two columns, corpus and background.

        >>> corpus.get_unigram_corpus().get_term_and_background_counts()
                          corpus  background
        obama              702.0    565739.0
        romney             570.0    695398.0
        barack             248.0    227861.0
        ...
        '''
        background_df = self._get_background_unigram_frequencies()
        corpus_freq_df = self.get_term_count_df()
        corpus_unigram_freq = self._get_corpus_unigram_freq(corpus_freq_df)
        df = corpus_unigram_freq.join(background_df, how='outer').fillna(0)
        del df.index.name
        return df