code: def _tau_b(A):
      """Calculate Kendall's tau-b and p-value from contingency table."""
      # See [2] 2.2 and 4.2
  
      # contingency table must be truly 2D
      if A.shape[0] == 1 or A.shape[1] == 1:
          return np.nan, np.nan
  
      NA = A.sum()
      PA = _P(A)
      QA = _Q(A)
      Sri2 = (A.sum(axis=1) ** 2).sum()
      Scj2 = (A.sum(axis=0) ** 2).sum()
      denominator = (NA**2 - Sri2) * (NA**2 - Scj2)
  
      tau = (PA - QA) / (denominator) ** 0.5
  
      numerator = 4 * (_a_ij_Aij_Dij2(A) - (PA - QA) ** 2 / NA)
      s02_tau_b = numerator / denominator
      if s02_tau_b == 0:  # Avoid divide by zero
          return tau, 0
      Z = tau / s02_tau_b**0.5
      p = 2 * norm.sf(abs(Z))  # 2-sided p-value
  
      return tau, p
  
imports: from collections import namedtuple
  from dataclasses import make_dataclass
  import numpy
  import warnings
  from itertools import combinations
  import scipy.stats
  from scipy.optimize import shgo
  from .None import distributions
  from ._continuous_distns import chi2, norm
  from scipy.special import gamma, kv, gammaln
  from .None import _wilcoxon_data
label_desc: Use image node_id 12 for calling a global function with example usage: _tau_b(A) and returns: tau,  p, np,  np, tau,  int