code: def data_loading(dataset):
      """
      data_loading allows shapash user to try the library with small but clear datasets.
      Titanic, house_prices or telco_customer_churn data.
  
      Example
      ----------
      >>> from shapash.data.data_loader import data_loading
      >>> house_df, house_dict = data_loading('house_prices')
  
      Parameters
      ----------
      dataset : String
          Dataset's name to return.
           - 'titanic'
           - 'house_prices'
           - 'telco_customer_churn'
  
      Returns
      -------
      data : pandas.DataFrame
          Dataset required
      dict : (Dictionnary, Optional)
          If exist, columns labels dictionnary associated to the dataset.
      """
      data_path = str(Path(__file__).parents[2] / "data")
      if dataset == "house_prices":
          github_data_url = (
              "https://github.com/MAIF/shapash/raw/master/data/"
          )
          data_house_prices_path = _find_file(
              data_path, github_data_url, "house_prices_dataset.csv"
          )
          dict_house_prices_path = _find_file(
              data_path, github_data_url, "house_prices_labels.json"
          )
          data = pd.read_csv(
              data_house_prices_path,
              header=0,
              index_col=0,
              engine="python",
          )
          if github_data_url in dict_house_prices_path:
              with urlopen(dict_house_prices_path) as openfile:
                  dic = json.load(openfile)
          else:
              with open(dict_house_prices_path, "r") as openfile:
                  dic = json.load(openfile)
          return data, dic
  
      elif dataset == "titanic":
          github_data_url = (
              "https://github.com/MAIF/shapash/raw/master/data/"
          )
          data_titanic_path = _find_file(
              data_path, github_data_url, "titanicdata.csv"
          )
          dict_titanic_path = _find_file(
              data_path, github_data_url, "titaniclabels.json"
          )
          data = pd.read_csv(
              data_titanic_path, header=0, index_col=0, engine="python"
          )
          if github_data_url in dict_titanic_path:
              with urlopen(dict_titanic_path) as openfile:
                  dic = json.load(openfile)
          else:
              with open(dict_titanic_path, "r") as openfile:
                  dic = json.load(openfile)
          return data, dic
  
      elif dataset == "telco_customer_churn":
          github_data_url = "https://github.com/IBM/telco-customer-churn-on-icp4d/raw/master/data/"
          data_telco_path = _find_file(
              data_path, github_data_url, "Telco-Customer-Churn.csv"
          )
          data = pd.read_csv(
              data_telco_path, header=0, index_col=0, engine="python"
          )
          return data
  
      elif dataset == "us_car_accident":
          github_data_url = (
              "https://github.com/MAIF/shapash/raw/master/data/"
          )
          data_accidents_path = _find_file(
              data_path, github_data_url, "US_Accidents_extract.csv"
          )
          data = pd.read_csv(
              data_accidents_path, header=0, engine="python"
          )
          return data
  
      else:
          raise ValueError(
              "Dataset not found. Check the docstring for available values"
          )
  
file_path: shapash/shapash/data/data_loader.py
imports: import os
  from pathlib import Path
  import json
  import pandas
  from urllib.request import urlopen
  from urllib.error import URLError
label_desc: Use image node_id 2 for calling a global function with example usage: data_loading(dataset) and returns: data,  dic, data,  dic, data, data