old_contents: # -*- coding: utf-8 -*-
  # modified from https://github.com/CamDavidsonPilon/lifelines/
  
  import pandas as pd
  from .. import utils
  from pkg_resources import resource_filename
  
  __all__ = [
      'load_cdnow_summary',
      'load_transaction_data',
      'load_cdnow_summary_data_with_monetary_value',
      'load_donations'
  ]
  
  
  def load_dataset(filename, **kwargs):
      '''
      Load a dataset from lifetimes.datasets
  
      Parameters:
      filename : for example "larynx.csv"
      usecols : list of columns in file to use
  
      Returns : Pandas dataframe
      '''
      return pd.read_csv(resource_filename('lifetimes', 'datasets/' + filename), **kwargs)
  
  
  def load_donations(**kwargs):
      return load_dataset('donations.csv', **kwargs)
  
  
  def load_cdnow_summary(**kwargs):
      return load_dataset('cdnow_customers_summary.csv', **kwargs)
  
  
  def load_transaction_data(**kwargs):
      """
      Returns a Pandas dataframe of transactional data. Looks like:
  
                        date  id
      0  2014-03-08 00:00:00   0
      1  2014-05-21 00:00:00   1
      2  2014-03-14 00:00:00   2
      3  2014-04-09 00:00:00   2
      4  2014-05-21 00:00:00   2
  
      The data was artificially created using Lifetimes data generation routines. Data was generated
      between 2014-01-01 to 2014-12-31.
  
      """
      return load_dataset('example_transactions.csv', **kwargs)
  
  
  def load_cdnow_summary_data_with_monetary_value(**kwargs):
      df = load_dataset('cdnow_customers_summary_transactions.csv', **kwargs)
      df.columns = ['customer_id', 'frequency', 'recency', 'T', 'monetary_value']
      df = df.set_index('customer_id')
      return df
  
new_contents: # -*- coding: utf-8 -*-
  # modified from https://github.com/CamDavidsonPilon/lifelines/
  
  import pandas as pd
  from .. import utils
  from pkg_resources import resource_filename
  
  __all__ = [
      'load_cdnow_summary',
      'load_transaction_data',
      'load_cdnow_summary_data_with_monetary_value',
      'load_donations'
  ]
  
  
  def load_dataset(filename, **kwargs):
      '''
      Load a dataset from lifetimes.datasets
  
      Parameters:
      filename : for example "larynx.csv"
      usecols : list of columns in file to use
  
      Returns : Pandas dataframe
      '''
      return pd.read_csv(resource_filename('lifetimes', 'datasets/' + filename), **kwargs)
  
  
  def load_donations(**kwargs):
      return load_dataset('donations.csv', **kwargs)
  
  
  def load_cdnow_summary(**kwargs):
      return load_dataset('cdnow_customers_summary.csv', **kwargs)
  
  
  def load_transaction_data(**kwargs):
      """
      Returns a Pandas dataframe of transactional data. Looks like:
  
                        date  id
      0  2014-03-08 00:00:00   0
      1  2014-05-21 00:00:00   1
      2  2014-03-14 00:00:00   2
      3  2014-04-09 00:00:00   2
      4  2014-05-21 00:00:00   2
  
      The data was artificially created using Lifetimes data generation routines. Data was generated
      between 2014-01-01 to 2014-12-31.
  
      """
      return load_dataset('example_transactions.csv', **kwargs)
  
  
  def load_cdnow_summary_data_with_monetary_value(**kwargs):
      df = load_dataset('cdnow_customers_summary_with_transactions.csv', **kwargs)
      df.columns = ['customer_id', 'frequency', 'recency', 'T', 'monetary_value']
      df = df.set_index('customer_id')
      return df
  
subject: fix typo