code: 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
  
imports: import numpy
  import pandas
  from scipy.stats import shapiro
  from scipy.stats import spearmanr
  from scipy.stats import kendalltau
  from sklearn_evaluation.telemetry import SKLearnEvaluationLogger
  from ploomber_core.exceptions import modify_exceptions
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: kendalltau(X) and returns: corrs