code: def plot_style_factor_exposures(tot_style_factor_exposure, factor_name=None,
                                  ax=None):
      
  
      if ax is None:
          ax = plt.gca()
  
      if factor_name is None:
          factor_name = tot_style_factor_exposure.name
  
      ax.plot(tot_style_factor_exposure.index, tot_style_factor_exposure,
              label=factor_name)
      avg = tot_style_factor_exposure.mean()
      ax.axhline(avg, linestyle='-.', label='Mean = {:.3}'.format(avg))
      ax.axhline(0, color='k', linestyle='-')
      _, _, y1, y2 = plt.axis()
      lim = max(abs(y1), abs(y2))
      ax.set(title='Exposure to {}'.format(factor_name),
             ylabel='{} \n weighted exposure'.format(factor_name),
             ylim=(-lim, lim))
      ax.legend(frameon=True, framealpha=0.5)
  
      return ax
docs: Plots DataFrame output of compute_style_factor_exposures as a line graph
  
      Parameters
      ----------
      tot_style_factor_exposure : pd.Series
          Daily style factor exposures (output of compute_style_factor_exposures)
          - Time series with decimal style factor exposures
          - Example:
              2017-04-24    0.037820
              2017-04-25    0.016413
              2017-04-26   -0.021472
              2017-04-27   -0.024859
  
      factor_name : string
          Name of style factor, for use in graph title
          - Defaults to tot_style_factor_exposure.name