new_contents: import numpy as np
  import matplotlib.pyplot as plt
  import pandas as pd
  
  
  s = pd.Series([1, 3, 5, np.nan, 8])
  print(s)
  print(s.index, s.values)
  
  """Creating DataFrame by passing numpy array"""
  dates = pd.date_range('20170404', periods=6)
  print(dates)
  print(np.random.randn(6, 4))
  df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
  print(df)
  
  """Creating DataFrame by passing dictionary"""
  data_dict = {
      'weekday': ['mon', 'tue', 'wed', 'thu'],
      'city': ['Austin', 'Dallas', 'LA', 'Boston'],
      'visitors': [123, 232, 334, 234],
  }
  print(pd.DataFrame(data_dict))
  
  """Creating DataFrame by passing list"""
  cities = ['Austin', 'Dallas', 'LA', 'Boston']
  weekdays = ['mon', 'tue', 'wed', 'thu']
  visitors = [123, 232, 334, 234]
  list_labels = ['city', 'visitors', 'weekday']
  list_cols = [cities, visitors, weekdays]
  zipped = list(zip(list_labels, list_cols))
  print(zipped)
  data_dict2 = dict(zipped)
  print(pd.DataFrame(data_dict2))
  
  """Broadcasting"""
  users = pd.DataFrame(data_dict)  # broadcasts to entire column
  users['fees'] = 0
  print(users)
  
  heights = [59.0, 64.2, 52.0, 62.0, 56.8]
  data_b = {'heights': heights, 'sex': 'M'}
  results = pd.DataFrame(data_b)
  print(results)
  results.columns = ['height (in)', 'sex']  # change index and column labels
  results.index = ['A', 'B', 'C', 'D', 'E']
  print(results)
  
  file_name = "http://www.ats.ucla.edu/stat/data/binary.csv"
  df3 = pd.read_csv(file_name)
  print(df3)
  
  # # Read in the file: df1
  # df1 = pd.read_csv('world_population.csv')
  # # Create a list of the new column labels: new_labels
  # new_labels = ['year', 'population']
  # # Read in the file, specifying the header and names parameters: df2
  # df2 = pd.read_csv('world_population.csv', header=0, names=new_labels)
  # # Print both the DataFrames
  # print(df1)
  # print(df2)
  #
  #
  # # Read the raw file as-is: df1
  # df1 = pd.read_csv(file_messy)
  # # Print the output of df1.head()
  # print(df1.head())
  # # Read in the file with the correct parameters: df2
  # df2 = pd.read_csv(file_messy, delimiter=' ', header=3, comment='#')
  # # Print the output of df2.head()
  # print(df2.head())
  # # Save the cleaned up DataFrame to a CSV file without the index
  # df2.to_csv(file_clean, index=False)
  # # Save the cleaned up DataFrame to an excel file without the index
  # df2.to_excel('file_clean.xlsx', index=False)
  
  
  
subject: Add assignment0