code: def dataset_initializer(request_info):
      dataset = request_info["df"]
      json_file_path = request_info["json"]
  
      if isinstance(json_file_path, str):
          json_file = read_json(json_file_path)
      else:
          json_file = json_file_path
  
      if "custom" not in json_file["data"]:
          if "target" not in json_file["data"]:
              raise Exception(
                  "A target column has to specified under the -- target -- keyword."
              )
          df = DataReader(json_file, dataset)
          df = df.data_reader()
  
      else:
          sys_path = "/nylon/supplementaries/buffer/"
          sys.path.insert(1, os.getcwd() + sys_path)
  
          absolute_path = (
              os.path.abspath(os.getcwd())
              + "/nylon/supplementaries/buffer/temp.py"
          )
  
          file_name = json_file["data"]["custom"]["loc"].rsplit("/")[-1]
          shutil.copy(json_file["data"]["custom"]["loc"], absolute_path)
  
          mod = import_module("temp")
          new_func = getattr(mod, json_file["data"]["custom"]["name"])
  
          df = new_func(json_file)
          sys.path.remove(sys_path)
          os.remove("./buffer/temp.py")
  
      request_info["df"] = df
      request_info["json"] = json_file
  
      return request_info
  
file_path: nylon/nylon/supplementaries/main.py
imports: from nylon.data.reader import DataReader
  import json
  from sklearn.metrics import accuracy_score
  from sklearn.linear_model import LinearRegression
  from sklearn.impute import SimpleImputer
  import shutil
  import sys
  from sklearn.model_selection import cross_val_score
  from sklearn.preprocessing import OneHotEncoder, StandardScaler, LabelEncoder
  from importlib import import_module
  import os
label_desc: Use image node_id 3 for calling a global function with example usage: dataset_initializer(request_info) and returns: request_info