import datetime
import csv


# Question 1
# ----------
# Using the csv data file users.csv aggregate app users as well as registration date by month. The count of app
# users should be one dictionary while the count of registration month should be another dictionary. There will be
# no checking or test harness so simply print your results to the console.
# Example:
# d1 = {
#    'RECEIPT_HOG': 3325,
#    'SHOPAROO': 38,
#    'RECEIPT_LOTTERY': 820,
#    'RECEIPT_BIN': 3208
# }
# d2 = {
#    'Jan': 3852,
#    'Feb': 38525,
#    etc...
# }
def bigdata():
    # Write code here
    pass


def main():
    bigdata()

if __name__ == '__main__':
    main()

import datetime
import csv


# Question 1
# ----------
# Using the csv data file users.csv aggregate app users as well as registration date by month. The count of app
# users should be one dictionary while the count of registration month should be another dictionary. There will be
# no checking or test harness so simply print your results to the console in the display_results function.
# Example:
# d1 = {
#    'RECEIPT_HOG': 3325,
#    'SHOPAROO': 38,
#    'RECEIPT_LOTTERY': 820,
#    'RECEIPT_BIN': 3208
# }
# d2 = {
#    'Jan': 3852,
#    'Feb': 38525,
#    etc...
# }
def bigdata():
    # Write code here
    pass


def display_results(d1, d2):
    # Write code here
    pass


def main():
    bigdata()

if __name__ == '__main__':
    main()

Add print function to demonstrate func calling
Add print function to demonstrate func calling

  import datetime
  import csv
  
  
  # Question 1
  # ----------
  # Using the csv data file users.csv aggregate app users as well as registration date by month. The count of app
  # users should be one dictionary while the count of registration month should be another dictionary. There will be
- # no checking or test harness so simply print your results to the console.
+ # no checking or test harness so simply print your results to the console in the display_results function.
  # Example:
  # d1 = {
  #    'RECEIPT_HOG': 3325,
  #    'SHOPAROO': 38,
  #    'RECEIPT_LOTTERY': 820,
  #    'RECEIPT_BIN': 3208
  # }
  # d2 = {
  #    'Jan': 3852,
  #    'Feb': 38525,
  #    etc...
  # }
  def bigdata():
      # Write code here
      pass
  
  
+ def display_results(d1, d2):
+     # Write code here
+     pass
+ 
+ 
  def main():
      bigdata()
  
  if __name__ == '__main__':
      main()
  
Add print function to demonstrate func calling
## Code Before:
import datetime
import csv


# Question 1
# ----------
# Using the csv data file users.csv aggregate app users as well as registration date by month. The count of app
# users should be one dictionary while the count of registration month should be another dictionary. There will be
# no checking or test harness so simply print your results to the console.
# Example:
# d1 = {
#    'RECEIPT_HOG': 3325,
#    'SHOPAROO': 38,
#    'RECEIPT_LOTTERY': 820,
#    'RECEIPT_BIN': 3208
# }
# d2 = {
#    'Jan': 3852,
#    'Feb': 38525,
#    etc...
# }
def bigdata():
    # Write code here
    pass


def main():
    bigdata()

if __name__ == '__main__':
    main()

## Instruction:
Add print function to demonstrate func calling
## Code After:
import datetime
import csv


# Question 1
# ----------
# Using the csv data file users.csv aggregate app users as well as registration date by month. The count of app
# users should be one dictionary while the count of registration month should be another dictionary. There will be
# no checking or test harness so simply print your results to the console in the display_results function.
# Example:
# d1 = {
#    'RECEIPT_HOG': 3325,
#    'SHOPAROO': 38,
#    'RECEIPT_LOTTERY': 820,
#    'RECEIPT_BIN': 3208
# }
# d2 = {
#    'Jan': 3852,
#    'Feb': 38525,
#    etc...
# }
def bigdata():
    # Write code here
    pass


def display_results(d1, d2):
    # Write code here
    pass


def main():
    bigdata()

if __name__ == '__main__':
    main()
