code: def load_outcome_not_last_column_dataset():
      data = [
          ["a", 0, 10],
          ["a", 0, 10000],
          ["a", 0, 14],
          ["a", 0, 10],
          ["a", 0, 10],
      ]
      return pd.DataFrame(
          data, columns=["Categorical", "Outcome", "Numerical"]
      )
  
imports: import os
  import pickle
  import shutil
  import zipfile
  from urllib.request import urlretrieve
  import numpy
  import pandas
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
  import dice_ml
label_desc: Use image node_id 5 for calling a global function with example usage: load_outcome_not_last_column_dataset() and returns: pd