docs: def kendalltau(X):
      """
      Accepts a matrix X and returns a correlation matrix so that each column
      is the variable and each row is the observations.
  
      Parameters
      ----------
      X : ndarray or DataFrame of shape n x m
          A matrix of n instances with m features
  
      """
      corrs = np.zeros((X.shape[1], X.shape[1]))
      for idx, cola in enumerate(X.T):
          for jdx, colb in enumerate(X.T):
              corrs[idx, jdx] = sp_kendalltau(cola,colb)[0]
      return corrs