code: def fix_dataframe_with_respect_for_nlu_issues(df1, df2):
      # When this issue is resolved, we can remove the usage of this function
      # https://github.com/JohnSnowLabs/nlu/issues/new
      # TODO there may be some changes in confidence and changes in column names after storing/loading
      # a model these issues in NLU which are not related to MLflow and to be fixed.
      # For now we are applying a hotfix here on the dataframes to make sure that the tests run the
      # way they should
      df1 = df1.drop(
          columns=[
              c
              for c in df1.columns
              if c not in df2.columns or "confidence" in c
          ]
      )
      df2 = df2.drop(
          columns=[
              c
              for c in df2.columns
              if c not in df1.columns or "confidence" in c
          ]
      )
  
      def lower_strings(df):
          for c in df.columns:
              try:
                  df[c] = df[c].str.lower()
              except Exception:
                  pass
          return df
  
      df1 = lower_strings(df1)
      df2 = lower_strings(df2)
      # TODO fix: column names may change before/after save and Confidences change
      df1.columns = [f"c_{i}" for i in range(len(df1.columns))]
      df2.columns = [f"c_{i}" for i in range(len(df2.columns))]
      return df1, df2
  
imports: import json
  import os
  from pathlib import Path
  from unittest import mock
  import pandas
  import pyspark
  import pytest
  from johnsnowlabs import nlp
  from packaging.version import Version
  import mlflow
  import mlflow.utils.file_utils
  from mlflow import pyfunc
  from mlflow.environment_variables import MLFLOW_DFS_TMP
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.pyfunc import spark_udf
  from mlflow.utils.environment import _mlflow_conda_env
  from mlflow.utils.file_utils import TempDir
  from tests.helper_functions import assert_register_model_called_with_local_model_path
label_desc: Use image node_id 3 for calling a global function with example usage: fix_dataframe_with_respect_for_nlu_issues(df1, df2) and returns: df1,  df2, df