code: def target_real_feature_real_test(x, y):
      """
      Calculate the feature significance of a real-valued feature to a real-valued target as a p-value.
      Use `Kendall's tau` from :func:`~scipy.stats.kendalltau` for this.
  
      :param x: the real-valued feature vector
      :type x: pandas.Series
  
      :param y: the real-valued target vector
      :type y: pandas.Series
  
      :return: the p-value of the feature significance test. Lower p-values indicate a higher feature significance.
      :rtype: float
      """
      __check_if_pandas_series(x, y)
      _check_for_nans(x, y)
  
      tau, p_value = stats.kendalltau(x, y, method="asymptotic")
      return p_value
  
file_path: tsfresh/tsfresh/feature_selection/significance_tests.py
imports: import warnings
  from builtins import str
  import numpy
  import pandas
  from scipy import stats
label_desc: Use image node_id 4 for calling a global function with example usage: target_real_feature_real_test(x, y) and returns: p_value