Returns a dataframe of all revision tags and their timestamps. It will have the columns:

         * date
         * rev

        :param branch: (optional, default 'master') the branch to work in
        :param limit: (optional, default None), the maximum number of revisions to return, None for no limit
        :param skip: (optional, default None), the number of revisions to skip. Ex: skip=2 returns every other revision, None for no skipping.
        :param num_datapoints: (optional, default=None) if limit and skip are none, and this isn't, then num_datapoints evenly spaced revs will be used
        :return: DataFrame

def revs(self, branch='master', limit=None, skip=None, num_datapoints=None):
        """
        Returns a dataframe of all revision tags and their timestamps. It will have the columns:

         * date
         * rev

        :param branch: (optional, default 'master') the branch to work in
        :param limit: (optional, default None), the maximum number of revisions to return, None for no limit
        :param skip: (optional, default None), the number of revisions to skip. Ex: skip=2 returns every other revision, None for no skipping.
        :param num_datapoints: (optional, default=None) if limit and skip are none, and this isn't, then num_datapoints evenly spaced revs will be used
        :return: DataFrame

        """

        if limit is None and skip is None and num_datapoints is not None:
            limit = sum(1 for _ in self.repo.iter_commits())
            skip = int(float(limit) / num_datapoints)
        else:
            if limit is None:
                limit = sys.maxsize
            elif skip is not None:
                limit = limit * skip

        ds = [[x.committed_date, x.name_rev.split(' ')[0]] for x in self.repo.iter_commits(branch, max_count=limit)]
        df = DataFrame(ds, columns=['date', 'rev'])

        if skip is not None:
            if skip == 0:
                skip = 1

            if df.shape[0] >= skip:
                df = df.ix[range(0, df.shape[0], skip)]
                df.reset_index()
            else:
                df = df.ix[[0]]
                df.reset_index()

        return df