text: import pandas as pd
  import requests
  import numpy as np
  import time
  import os
  
  # Load station information
  station_url = "https://gbfs.capitalbikeshare.com/gbfs/en/station_information.json"
  stations = requests.get(station_url).json()
  station_df = pd.DataFrame(stations['data']['stations'])
  station_df = station_df[['lat', 'lon', 'region_id', 'short_name']].copy()
  # Default any missing region ids to DC (only example as of 2/21 is new station at Anacostia Park)
  station_df['region_id'] = np.where(
      station_df['region_id'].isnull(), 42, station_df['region_id'])
  
  # Convert region_id to str from float
  station_df['region_id'] = station_df['region_id'].astype(int).astype(str)
  
  # Load region information
  region_url = "https://gbfs.capitalbikeshare.com/gbfs/en/system_regions.json"
  regions = requests.get(region_url).json()
  regions_df = pd.DataFrame(regions['data']['regions'])
  
  # Merge region information onto stations
  station_df = station_df.merge(
      regions_df, left_on='region_id', right_on='region_id', how='left')
  station_df.rename(index=str, columns={'name': 'region_name'}, inplace=True)
  print(len(station_df))
  print(station_df['region_name'].value_counts())
  
  # Define Abbreviations for each region
  
  region_code = {'Washington, DC': 'WDC',
                 'Arlington, VA': 'ARL',
                 'Montgomery County, MD (South)': 'MCS',
                 'Montgomery County, MD (North)': 'MCN',
                 'Alexandria, VA': 'ALX',
                 'Fairfax, VA': 'FFX'}
  
  region_code_series = pd.Series(region_code, name='region_code')
  region_code_series.index.name = 'region_name'
  region_code_df = region_code_series.reset_index()
  station_df = station_df.merge(
      region_code_df, left_on='region_name', right_on='region_name', how='left')
  station_df.drop(['region_name', 'region_id'], inplace=True, axis=1)
  
  # Output DataFrame as CSV with timestamp
  TIMESTR = time.strftime("%Y%m%d_%H%M%S")
  filename = "CABI_Station_Info_" + TIMESTR + ".csv"
  filepath = os.path.join("./Output", filename)
  station_df.to_csv(filepath, index=False)
  