View difference between Paste ID: VU4M6zZY and esgq4R0i

 """
 Troy Goda - inclass9.py
 Algorithm
 Define function called makeAverage(student,key):
     take student[key] and store as scores
     Set total to 0
     for score in scores:
        set total = total + score
     take total and divide by length of scores, store as average
     return average
 import json
 Ask user to enter name of JSON file to process, store handle as filename and strip whitespace + \
     and force to lowercase letters
 open filename for reading, store handle as infile
 use json.loadstring, read all lines in infile, and store in list called mydictionary
 take ["students"] key of mydictionary, store as studentsList
 for student in studentsList:
     print student["name"] + "," + " hw average: " + str(makeAverage(student,"hwscores")) + "," + \
         + " exam average: " + str(makeAverage(student,"exams"))
 1)
-    One reason that JSON files are better than CSV is because JSON files are processed much more easily
+  One reason that JSON files are better than CSV is because JSON files are processed much more easily
-    and efficiently than CSV.  For this assignment, a CSV file would have 7 different data seperated by commas,
+and efficiently than CSV.  For this assignment, a CSV file would have 7 different data separated by
-    and you either need to label each score, or you might not process the data correctly.  You would have to
+commas,and you either need to label each score, or you might not process the data correctly.  You would
-    split the list and then identify which tokens goes to name, every hwscores, and every exam score.
+have to split the list and then identify which tokens goes to name, every hwscores, and every exam score.
-    This is much slower than using a JSON file where you can just take the keys "name", "hwscores",
+This is much slower than using a JSON file where you can just take the keys "name", "hwscores","exams",
-    "exams", and automatically get the data you want.  You also need to convert all of the hwscores
+and automatically get the data you want.  You also need to convert all of the hwscores and exam scores
-    and exam scores to a number, because in a CSV file list they are strings.
+to a number, because in a CSV file list they are strings. Another reason is that you can have a
-    Another reason is that you can have a hierachy data, like an xml, but in a much easier and simpler
+hierarchy data, like an XML, but in a much easier and simpler form to process and read the file.
-    form to process and read the file.
+
 Jane Doe,85.1,95.0,95.0,92.7,91.4,95.2
 John Doe,95.1,90.5,90.1,91.1,81.3,85.6
 Bill Gates,60,60,75,98.7,94.4,96.4
 
 """
 def makeAverage(student,key):
     scores = student[key]
     total = 0
     for score in scores:
         total += score
     average = total / len(scores)
     return average
 import json
 filename = raw_input("Enter name of JSON file to process: ").strip().lower()
 #filename = "studentscores.json"
 infile = open(filename,"r")
 mydictionary = json.loads(infile.read())
 studentsList = mydictionary["students"]
 for student in studentsList:
     print student["name"] + "," + " hw average: " + str(makeAverage(student,"hwscores")) + "," + \
-    print student["name"] + "," + " hw average: " + str(makeAverage(student,"hwscores")) + "," + " exam average: " + str(makeAverage(student,"exams"))
+        + " exam average: " + str(makeAverage(student,"exams"))