code: def test_data_c_likelihood(train_data_discrete_cpds) -> pd.DataFrame:
      """Marginal likelihoods for train_data in train_model"""
  
      data_arr = [
          [
              (train_data_discrete_cpds["c"])[y, x]
              for y in range(len(train_data_discrete_cpds["c"]))
          ]
          for x in range(len(train_data_discrete_cpds["c"][0]))
      ]
  
      likelihood = pd.DataFrame(
          data_arr, columns=["c_0", "c_1", "c_2", "c_3", "c_4"]
      )
      return likelihood
  
imports: import itertools
  from typing import Dict
  import numpy
  import pandas
  import pytest
  from pgmpy.models import BayesianNetwork
  from sklearn.datasets import load_iris
  from causalnex.discretiser import Discretiser
  from causalnex.network import BayesianNetwork
  from causalnex.structure import StructureModel
  from causalnex.structure.notears import from_pandas
label_desc: Use image node_id 15 for calling a global function with example usage: test_data_c_likelihood(train_data_discrete_cpds) and returns: likelihood