docs: def create_full_tear_sheet(factor_data,
                             long_short=True,
                             group_neutral=False,
                             by_group=False):
      """
      Creates a full tear sheet for analysis and evaluating single
      return predicting (alpha) factor.
  
      Parameters
      ----------
      factor_data : pd.DataFrame - MultiIndex
          A MultiIndex DataFrame indexed by date (level 0) and asset (level 1),
          containing the values for a single alpha factor, forward returns for
          each period, the factor quantile/bin that factor value belongs to, and
          (optionally) the group the asset belongs to.
          - See full explanation in utils.get_clean_factor_and_forward_returns
      long_short : bool
          Should this computation happen on a long short portfolio?
          - See tears.create_returns_tear_sheet for details on how this flag
          affects returns analysis
      group_neutral : bool
          Should this computation happen on a group neutral portfolio?
          - See tears.create_returns_tear_sheet for details on how this flag
          affects returns analysis
          - See tears.create_information_tear_sheet for details on how this
          flag affects information analysis
      by_group : bool
          If True, display graphs separately for each group.
      """
  
      plotting.plot_quantile_statistics_table(factor_data)
      create_returns_tear_sheet(factor_data,
                                long_short,
                                group_neutral,
                                by_group,
                                set_context=False)
      create_information_tear_sheet(factor_data,
                                    group_neutral,
                                    by_group,
                                    set_context=False)
      create_turnover_tear_sheet(factor_data, set_context=False)