code: def test_normalize_dataframe_loses_column_metadata(es):
      es["log"].ww.columns["value"].metadata["interesting_values"] = [
          0.0,
          1.0,
      ]
      es["log"].ww.columns["priority_level"].metadata[
          "interesting_values"
      ] = [1]
  
      es["log"].ww.columns["value"].description = "a value column"
      es["log"].ww.columns[
          "priority_level"
      ].description = "a priority level column"
  
      assert (
          "interesting_values"
          in es["log"].ww.columns["priority_level"].metadata
      )
      assert (
          "interesting_values" in es["log"].ww.columns["value"].metadata
      )
      assert (
          es["log"].ww.columns["value"].description == "a value column"
      )
      assert (
          es["log"].ww.columns["priority_level"].description
          == "a priority level column"
      )
  
      es.normalize_dataframe(
          "log",
          "values_2",
          "value_2",
          additional_columns=["priority_level"],
          copy_columns=["value"],
          make_time_index=False,
      )
  
      # Metadata in the original dataframe and the new dataframe are maintained
      assert (
          "interesting_values" in es["log"].ww.columns["value"].metadata
      )
      assert (
          "interesting_values"
          in es["values_2"].ww.columns["value"].metadata
      )
      assert (
          "interesting_values"
          in es["values_2"].ww.columns["priority_level"].metadata
      )
      assert (
          es["log"].ww.columns["value"].description == "a value column"
      )
      assert (
          es["values_2"].ww.columns["value"].description
          == "a value column"
      )
      assert (
          es["values_2"].ww.columns["priority_level"].description
          == "a priority level column"
      )
  
imports: from datetime import datetime
  import numpy
  import pandas
  import pytest
  from woodwork.exceptions import TypeConversionError
  from woodwork.logical_types import Boolean, Categorical, Datetime, Double, Integer, NaturalLanguage
  from featuretools.entityset.entityset import LTI_COLUMN_NAME, EntitySet
  from featuretools.tests.testing_utils import to_pandas
  from featuretools.utils.gen_utils import Library, import_or_none, is_instance
label_desc: Use image node_id 52 for calling a global function with example usage: test_normalize_dataframe_loses_column_metadata(es) without return types