old_contents: # some wrapped functions from seaborn
  import numpy as np
  import scipy.stats as st
  
  def regplot(x, y, hue=None, hue_values=None, show_corr=True, **kwargs):
      """Wrap plot of `seaborn.regplot` with supporting hue and showing 
      correlation coeffecient.
  
      Parameters
      ----------
      x: `array_like`, (1, ) for values on x-axis
      y: `array_like`, (1, ) for values on y-axis
      hue: `array_like`, (1, )
          Values to stratify samples into different groups
      hue_values: list or `array_like`
          A list of unique hue values; orders are kept in layers
      show_corr: bool
          Whether show Pearson's correlation coefficient in legend
      **kwargs: for `seaborn.regplot`
      """
      import seaborn
      if hue is None:
          if show_corr:
              _label = "R=%.2f" %(st.pearsonr(x, y)[0])
          else:
              _label = None
          seaborn.regplot(x, y, label=_label, **kwargs)
      else:
          if hue_values is None:
              hue_values = np.unique(hue)
          for hue_val in hue_values:
              _idx = hue == hue_val
              if show_corr:
                  _label = str(hue_val) + ": R=%.2f" %(
                      st.pearsonr(x[_idx], y[_idx])[0])
              else:
                  _label = None
              seaborn.regplot(x[_idx], y[_idx], label=_label, **kwargs)
      
new_contents: # some wrapped functions from seaborn
  import numpy as np
  import scipy.stats as st
  import matplotlib.pyplot as plt
  
  def regplot(x, y, hue=None, hue_values=None, show_corr=True, legend_on=True,
              **kwargs):
      """Wrap plot of `seaborn.regplot` with supporting hue and showing 
      correlation coeffecient.
  
      Parameters
      ----------
      x: `array_like`, (1, ) for values on x-axis
      y: `array_like`, (1, ) for values on y-axis
      hue: `array_like`, (1, )
          Values to stratify samples into different groups
      hue_values: list or `array_like`
          A list of unique hue values; orders are kept in layers
      show_corr: bool
          Whether show Pearson's correlation coefficient in legend
      **kwargs: for `seaborn.regplot`
      """
      import seaborn
      if hue is None:
          if show_corr:
              _label = "R=%.2f" %(st.pearsonr(x, y)[0])
          else:
              _label = None
          seaborn.regplot(x, y, label=_label, **kwargs)
      else:
          if hue_values is None:
              hue_values = np.unique(hue)
          for hue_val in hue_values:
              _idx = hue == hue_val
              if show_corr:
                  _label = str(hue_val) + ": R=%.2f" %(
                      st.pearsonr(x[_idx], y[_idx])[0])
              else:
                  _label = None
              seaborn.regplot(x[_idx], y[_idx], label=_label, **kwargs)
      
      if legend_on:
          plt.legend()
      
subject: add legend_on for regplot