code: def get_min_depend_from_matrix(depend_matrix, variables_list):
      _vars_min_depend = []
      _min_depend = []
      for vars in variables_list:
          if isinstance(vars, (list, tuple, np.ndarray)):
              depend_submatrix = abs(depend_matrix).loc[
                  list(vars), list(vars)
              ]
              _min = np.array(depend_submatrix).min()
              _min_idx = np.where(depend_submatrix == _min)
              var_a_idx, var_b_idx = _min_idx[0][0], _min_idx[1][0]
              _vars_min_depend.append(
                  np.array(
                      depend_submatrix.columns[[var_a_idx, var_b_idx]]
                  )
              )
              _min_depend.append(_min)
          else:
              _vars_min_depend.append(None)
              _min_depend.append(None)
      return _vars_min_depend, _min_depend
  
file_path: DALEX/python/dalex/dalex/aspect/utils.py
imports: import numpy
  import pandas
  import warnings
  from .None import checks
  from ..None import _global_checks
label_desc: Use image node_id 8 for calling a global function with example usage: get_min_depend_from_matrix(depend_matrix, variables_list) and returns: _vars_min_depend,  _min_depend