content: import pandas as pd
  import numpy as np
  from matplotlib import pyplot as plt
  import os
  
  from pygeocoder import Geocoder
  
  plt.ion()
  
  year = 2015
  record_num = []
  
  aggregation_rule = {'Sum': sum}
  
  ts_all = None
  
  aggregation_window = "1min"
  print " aggregate data at" + aggregation_window + "resolution"
  
  for year in [2014, 2015]:
    for month in xrange(1, 13):
      datafileName = 'yellow_tripdata_' + str(year) + '-' + "{:0>2d}".format(month) + '.csv'
  
      if os.path.isfile(datafileName):
        print " Load Datafile: ", datafileName
        # df = pd.read_csv(datafileName, header=0, nrows=100,  usecols=[1, 3, 5, 6],
        #                  names=['pickup_datetime', 'passenger_count', 'pickup_longitude', 'pickup_latitude'])
        #
        # postcode = np.zeros(len(df))
        # for i in xrange(len(df)):
        #   try:
        #     results = Geocoder.reverse_geocode(df['pickup_latitude'][i], df['pickup_longitude'][i])
        #     postcode[i] = results.postal_code
        #   except:
        #     pass
  
  
        df = pd.read_csv(datafileName, header=0, usecols=[1, 3], names=['pickup_datetime', 'passenger_count'])
  
        record_num.append(len(df))
  
        ts = pd.Series(np.array(df.passenger_count), index=pd.to_datetime(df.pickup_datetime))
        del df
  
        ts_aggregate = ts.resample(aggregation_window, how=aggregation_rule)
  
        if ts_all is not None:
          print " concat ts_all"
          ts_all = pd.concat([ts_all, ts_aggregate])
        else:
          print " initialize ts_all"
          ts_all = ts_aggregate
      else:
        print datafileName, " not exist"
  
  
  print "include time of day and day of week as input field"
  date = ts_all.index
  dayofweek = (date.dayofweek)
  timeofday = (date.hour*60 + date.minute)
  passenger_count = np.array(ts_all['Sum'])
  seq = pd.DataFrame(np.transpose(np.array([passenger_count, timeofday, dayofweek])), columns=['passenger_count', 'timeofday', 'dayofweek'], index=ts_all.index)
  
  plt.close('all')
  plt.figure(1)
  plt.plot(seq.index, seq.passenger_count)
  
  import csv
  outputFileName = "nyc_taxi_" + aggregation_window + ".csv"
  outputFile = open(outputFileName,"w")
  csvWriter = csv.writer(outputFile)
  csvWriter.writerow(['timestamp', 'passenger_count', 'timeofday', 'dayofweek'])
  csvWriter.writerow(['datetime', 'int', 'int', 'string'])
  csvWriter.writerow(['T', '', '', ''])
  for i in range(len(ts_all)):
    csvWriter.writerow([seq.index[i], seq.passenger_count[i], seq.timeofday[i], seq.dayofweek[i]])
  outputFile.close()