docstr: Test the normalize dict on 'none' and 'na_categorical'.
docstr_tok: ["Test","the","normalize","dict","on","'none","'","and","'na_categorical","'","."]
code: def test_count_normalize_dict(self):
      """Test the normalize dict on 'none' and 'na_categorical'."""
      enc = encoders.CountEncoder(
          min_group_size=7,
          normalize={"none": True, "na_categorical": False},
      )
  
      enc.fit(X)
      out = enc.transform(X_t)
  
      self.assertIn("none", enc._normalize)
      self.assertTrue(
          out["none"].round(5).isin([0.3, 0.15, 0.25]).all()
      )
      self.assertEqual(out["none"].unique().shape[0], 3)
      self.assertEqual(out["none"].isna().sum(), 0)
      self.assertTrue(
          pd.Series([13, 7]).isin(out["na_categorical"]).all()
      )
      self.assertEqual(out["na_categorical"].unique().shape[0], 2)
      self.assertTrue(enc.mapping is not None)
  
file_path: category_encoders/tests/test_count.py
imports: import pandas
  from unittest import TestCase
  import numpy
  import category_encoders
label_desc: Use image node_id 13 for calling the TestCountEncoder obj's underlying member method code with example usage: obj.test_count_normalize_dict() without return types