text: #!/usr/bin/python
  
  # The usual preamble
  import numpy as np
  import pandas as pd
  import time
  
  # Get data (NYC 311 service request dataset) and start cleanup
  na_values = ['NO CLUE', 'N/A', '0']
  requests = pd.read_csv('data/311-service-requests.csv',
                         na_values=na_values, dtype={'Incident Zip': str})
  print "Done reading input file..."
  
  start = time.time()
  
  # Fix requests with extra digits
  requests['Incident Zip'] = requests['Incident Zip'].str.slice(0, 5)
  
  # Fix requests with 00000 zipcodes
  zero_zips = requests['Incident Zip'] == '00000'
  requests['Incident Zip'][zero_zips] = np.nan
  
  # Display unique incident zips again (this time cleaned)
  print requests['Incident Zip'].unique()
  end = time.time()
  
  print "Total end-to-end time: %.2f" % (end - start)
  