76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
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MAX = 45
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classes = {}
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def mean(x):
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return sum(x) / len(x)
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def median(x):
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n = len(x)
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i = n // 2
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if n % 2:
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return sorted(x)[i]
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return sum(sorted(x)[i - 1:i + 1]) / 2
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# Read the data file
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data = open('marks.csv')
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lines = data.readlines()
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for line in lines:
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# Figure out the name of the class
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lineNumber = lines.index(line) + 1
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className = 'Class ' + str(lineNumber)
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# Parse the csv to figure out the marks for each class
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marks = line.split(',')
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for i in marks:
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index = marks.index(i)
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marks[index] = int(i) # Ensure all of the marks are formatted as integers
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# Ensure that the max amount of marks is not breached
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for i in marks:
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if i > MAX:
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raise Exception('Line/Class {0} contains a mark higher than the max attainable ({1})'.format(str(lineNumber), str(MAX)))
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# Initialise the class dictionary, and assign the marks value
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classes[className] = {}
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classes[className]['marks'] = marks
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# Calculate the mean and median for each class
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classes[className]['mean'] = mean(marks)
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classes[className]['median'] = median(marks)
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# Calculate how many students are above and below the median
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above = 0
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below = 0
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for i in marks:
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if i > classes[className]['median']:
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above += 1
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elif i < classes[className]['median']:
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below += 1
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classes[className]['aboveMedian'] = above
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classes[className]['belowMedian'] = below
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# Find the class with the highest mean
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allMeans = []
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for i in classes:
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allMeans.append(classes[i]['mean']) # Put all of the means into a list
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highestMean = max(allMeans) # Find the highest of those means
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for i in classes:
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for k, v in classes[i].items():
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if k == 'mean' and v == highestMean: # Find the matching key and value
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highestMean = i # Set the highestMean to the class name
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# Find the median across all classes
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allMarks = []
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for i in classes:
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allMarks += classes[i]['marks'] # Concatenate all marks lists
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medianAcross = median(allMarks) # Find the median of that concatenated list
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# Output
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print('Results!\n-----------')
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for i in classes:
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c = classes[i]
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print('{0}:\n\nMean: {1}\nMedian: {2}\nAbove Median: {3}\nBelow Median: {4}\n-----------'.format(i, str(c['mean']), str(c['median']), str(c['aboveMedian']), str(c['belowMedian'])))
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print('\nClass with the highest mean mark: {0}\nMedian mark across all classes: {1}'.format(str(highestMean), str(medianAcross)))
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