text: '''
  Dictionaries for data science
  100xp
  
  For this exercise, you'll use what you've learned about the zip() function and combine two
  lists into a dictionary.
  
  These lists are actually extracted from a bigger dataset file of world development indicators
  from the World Bank. For pedagogical purposes, we have pre-processed this dataset into the lists
  that you'll be working with.
  
  The first list feature_names contains header names of the dataset and the second list row_vals
  contains actual values of a row from the dataset, corresponding to each of the header names.
  
  Instructions
  -Create a zip object by calling zip() and passing to it feature_names and row_vals. Assign the
  result to zipped_lists.
  -Create a dictionary from the zipped_lists zip object by calling dict() with zipped_lists.
  Assign the resulting dictionary to rs_dict.
  '''
  # Pre-defined lists
  feature_names = ['CountryName', 'CountryCode',
                   'IndicatorName', 'IndicatorCode', 'Year', 'Value']
  
  row_vals = ['Arab World', 'ARB',
                  'Adolescent fertility rate (births per 1,000 women ages 15-19)', 'SP.ADO.TFRT',
                  '1960', '133.56090740552298']
  
  # Zip lists: zipped_lists
  zipped_lists = zip(feature_names, row_vals)
  
  # Create a dictionary: rs_dict
  rs_dict = dict(zipped_lists)
  
  # Print the dictionary
  print(rs_dict)
  