old_contents: import pandas as pd
  crashes = pd.read_csv('./CAR-CRASHES-2007.csv', parse_dates=['DT_ACCDN'])
  interesting_columns = ['DT_ACCDN',
   'HR_ACCDN',
  # 'CD_ETAT_VICTM',
  # 'CD_MUNCP',
  # 'CIVIC_NUMBER',
  # 'RUE_ACCN_TYPE',
   'RUE_ACCDN',
  # 'RUE_ACCDN_DIR',
  # 'PRES_DE_TYPE',
   'ACCDN_PRES_DE',
  # 'ACCDN_PRES_DIR',
   'Address concatenation',
  # 'Geocoding address',
  # 'LATITUDE',
  # 'LONGITUDE',
   'NB_MORT_C',
   'NB_BLESE_GRAVE_C',
   'NB_BLESE_LEGER_C']
  crashes[interesting_columns].rename(columns={'DT_ACCDN': 'Date',
   'HR_ACCDN': 'Time',
   'CD_ETAT_VICTM': 'Victim count',
  # 'CD_MUNCP',
  # 'CIVIC_NUMBER',
  # 'RUE_ACCN_TYPE',
   'RUE_ACCDN': 'Street',
  # 'RUE_ACCDN_DIR',
  # 'PRES_DE_TYPE',
   'ACCDN_PRES_DE': 'Cross Street',
  # 'ACCDN_PRES_DIR',
   'Address concatenation': 'Address',
  # 'Geocoding address',
  # 'LATITUDE',
  # 'LONGITUDE',
   'NB_MORT_C': 'Deaths',
   'NB_BLESE_GRAVE_C': 'Serious Injuries',
   'NB_BLESE_LEGER_C': 'Injuries'}).to_csv('car_crashes_2007.csv', index=False)
  
new_contents: import pandas as pd
  crashes = pd.read_csv('./CAR-CRASHES-2007.csv', parse_dates=['DT_ACCDN'])
  remappings = {
      'DT_ACCDN': 'Date',
      'HR_ACCDN': 'Time',
      'CD_ETAT_VICTM': 'Victim count',
      # 'CD_MUNCP',
      # 'CIVIC_NUMBER',
      # 'RUE_ACCN_TYPE',
      'RUE_ACCDN': 'Street',
      # 'RUE_ACCDN_DIR',
      # 'PRES_DE_TYPE',
      'ACCDN_PRES_DE': 'Cross Street',
      # 'ACCDN_PRES_DIR',
      'Address concatenation': 'Address',
      # 'Geocoding address',
      'LATITUDE': 'Latitude',
      'LONGITUDE': 'Latitude',
      'NB_MORT_C': 'Deaths',
      'NB_BLESE_GRAVE_C': 'Serious Injuries',
      'NB_BLESE_LEGER_C': 'Injuries'}
  crashes = crashes[remappings.keys()].rename(columns=remappings)
  crashes['Intersection'] = crashes['Street'] + ' / ' + crashes['Cross Street']
  crashes.to_csv('car_crashes_2007.csv', index=False)
  
subject: fix fixup.py