docs: def plot_pair(df, feature_name_1, feature_name_2, kind='scatter', alpha=0.01, **kwargs):
      """
      Plot a scatterplot of two features against one another,
      and calculate Pearson correlation coefficient.
  
      Examples:
          `plot_pair(X, 'emb_mean_euclidean', 'emb_mean_cosine')`
  
      Args:
          df:
          feature_name_1: The name of the first feature.
          feature_name_2: The name of the second feature.
          kind: One of the values { 'scatter' | 'reg' | 'resid' | 'kde' | 'hex' }.
          alpha: Alpha channel value.
          **kwargs: Additional argument to 'sns.jointplot'.
      """
  
      plt.figure()
      sns.jointplot(
          feature_name_1,
          feature_name_2,
          df,
          alpha=alpha,
          kind=kind,
          **kwargs
      )
      plt.show()