docs: def commit_history(self, branch, limit=None, days=None, ignore_globs=None, include_globs=None):
          """
          Returns a pandas DataFrame containing all of the commits for a given branch. The results from all repositories
          are appended to each other, resulting in one large data frame of size <limit>.  If a limit is provided, it is
          divided by the number of repositories in the project directory to find out how many commits to pull from each
          project. Future implementations will use date ordering across all projects to get the true most recent N commits
          across the project.
  
          Included in that DataFrame will be the columns:
  
           * repository
           * date (index)
           * author
           * committer
           * message
           * lines
           * insertions
           * deletions
           * net
  
          :param branch: the branch to return commits for
          :param limit: (optional, default=None) a maximum number of commits to return, None for no limit
          :param days: (optional, default=None) number of days to return if limit is None
          :param ignore_globs: (optional, default=None) a list of globs to ignore, default none excludes nothing
          :param include_globs: (optinal, default=None) a list of globs to include, default of None includes everything.
          :return: DataFrame
          """
  
          if limit is not None:
              limit = int(limit / len(self.repo_dirs))
  
          df = pd.DataFrame(columns=['author', 'committer', 'message', 'lines', 'insertions', 'deletions', 'net'])
  
          for repo in self.repos:
              try:
                  ch = repo.commit_history(branch, limit=limit, days=days, ignore_globs=ignore_globs, include_globs=include_globs)
                  ch['repository'] = repo.repo_name
                  df = df.append(ch)
              except GitCommandError:
                  print('Warning! Repo: %s seems to not have the branch: %s' % (repo, branch))
  
          df.reset_index()
  
          return df