code: def test_ignore_variable_format_with_frequency(df_vartypes):
      encoder = CountFrequencyEncoder(
          encoding_method="frequency",
          variables=None,
          ignore_format=True,
      )
      X = encoder.fit_transform(df_vartypes)
  
      # expected output
      transf_df = {
          "Name": [0.25, 0.25, 0.25, 0.25],
          "City": [0.25, 0.25, 0.25, 0.25],
          "Age": [0.25, 0.25, 0.25, 0.25],
          "Marks": [0.25, 0.25, 0.25, 0.25],
          "dob": [0.25, 0.25, 0.25, 0.25],
      }
  
      transf_df = pd.DataFrame(transf_df)
  
      # init params
      assert encoder.encoding_method == "frequency"
      assert encoder.variables is None
      # fit params
      assert encoder.variables_ == [
          "Name",
          "City",
          "Age",
          "Marks",
          "dob",
      ]
      assert encoder.n_features_in_ == 5
      # transform params
      pd.testing.assert_frame_equal(X, transf_df)
  
imports: import warnings
  import numpy
  import pandas
  import pytest
  from numpy import nan
  from feature_engine.encoding import CountFrequencyEncoder
label_desc: Use image node_id 12 for calling a global function with example usage: test_ignore_variable_format_with_frequency(df_vartypes) without return types