code: def readDataSet(dataSet, noise=0):
    
    filePath = 'data/'+dataSet+'.csv'
  
    if dataSet == 'nyc_taxi' or dataSet == 'nyc_taxi_perturb' or dataSet == 'nyc_taxi_perturb_baseline':
      seq = pd.read_csv(filePath, header=0, skiprows=[1, 2], names=['time', 'data', 'timeofday', 'dayofweek'])
      seq['time'] = pd.to_datetime(seq['time'])
  
      if noise > 0:
        for i in xrange(len(seq)):
          value = seq['data'][i]
          noiseValue = np.random.normal(scale=(value * noise))
          value += noiseValue
          value = max(0, value)
          value = min(40000, value)
          seq['data'][i] = value
    # elif dataSet == 'sine':
    #   df = pd.read_csv(filePath, header=0, skiprows=[1, 2], names=['time', 'data'])
    #   sequence = df['data']
    #   seq = pd.DataFrame(np.array(sequence), columns=['data'])
    else:
      raise(' unrecognized dataset type ')
  
    return seq
docs: :param dataSet: dataset name
    :param noise: amount of noise added to the dataset
    :return: