code: def load_regression_data():
      dataset = fetch_california_housing(
          data_home="data", as_frame=True
      )
      df = dataset.frame.sample(5000)
      df["HouseAgeBin"] = pd.qcut(df["HouseAge"], q=4)
      df["HouseAgeBin"] = "age_" + df.HouseAgeBin.cat.codes.astype(str)
      test_idx = df.sample(int(0.2 * len(df)), random_state=42).index
      test = df[df.index.isin(test_idx)]
      train = df[~df.index.isin(test_idx)]
      return (train, test, dataset.target_names)
  
file_path: pytorch_tabular/tests/conftest.py
imports: import os.path
  from zipfile import ZipFile
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import fetch_california_housing, fetch_covtype
label_desc: Use image node_id 1 for calling a global function with example usage: load_regression_data() and returns: train,  test,  dataset