code: def download_har_dataset(folder_name=data_file_name):
      """
      Download human activity recognition dataset from UCI ML Repository and store it at /tsfresh/notebooks/data.
  
      Examples
      ========
  
      >>> from tsfresh.examples import har_dataset
      >>> har_dataset.download_har_dataset()
      """
  
      zipurl = "https://github.com/MaxBenChrist/human-activity-dataset/blob/master/UCI%20HAR%20Dataset.zip?raw=True"
  
      if not os.access(module_path, os.W_OK):
          raise RuntimeError(
              "You don't have the necessary permissions to download the Human Activity Dataset "
              "Set into the module path. Consider installing the module in a virtualenv you "
              "own or run this function with appropriate permissions."
          )
  
      if os.path.exists(os.path.join(folder_name, "UCI HAR Dataset")):
          _logger.warning(
              "You have already downloaded the Human Activity Data Set."
          )
          return
  
      os.makedirs(folder_name, exist_ok=True)
  
      r = requests.get(zipurl, stream=True)
      if r.status_code != 200:
          raise RuntimeError(
              "Could not download the Human Activity Data Set from GitHub."
              "HTTP status code: {}".format(r.status_code)
          )
  
      with ZipFile(BytesIO(r.content)) as zfile:
          zfile.extractall(path=folder_name)
  
file_path: tsfresh/tsfresh/examples/har_dataset.py
imports: import logging
  import os
  import shutil
  from io import BytesIO
  from zipfile import ZipFile
  import pandas
  import requests
label_desc: Use image node_id 1 for calling a global function with example usage: download_har_dataset(folder_name) without return types