UWA, like every university around the country needs to deal with marks of the students in different courses. For the analysis of university’s performance, management needs to have a computer program which can read the data from a csv (comma separated values) file and return different statistical aspects of the marks of the students and their ranking.
Your task is to write a program which follow the following specifications.
Input:
Your program must define the function main with the following signature:
def main(csvfile):
The input argument is the name of the csv file containing information and marks of the students which needs to be analysed. The first row of the csv file will contain the headers. From the second row, the first and second values of each row contain the names and any other information of the students. From third value onwards, it contains the marks student obtained in each subject. We do not have prior knowledge about the number of students and subjects available in the csv file.
Output:
The function is required to return the following outputs in the order provided below:
- List containing the minimum marks for each subject followed by minimum total marks obtained by a student. The order of the subjects should be same as the order of the subjects in the header row.
- List similar to above containing the maximum marks.
- List similar to above containing the average marks.
- List similar to above containing the standard deviations in marks.
- List similar to above containing the correlation of the ranks of the subject marks and total marks. The highest mark will be ranked as ‘1’, the second highest mark will be ranked ‘2’ and so on. If two or more students get the same marks then they should be ranked according to their names in alphabetical order. Two students cannot have the same rank for a course or total marks which means two student cannot be with the same name and marks. Use Spearman’s rank correlation coefficient for calculating the correlation of rankings.
All returned lists must contain numerical values rounded to four decimal places. Remember not to round the values during calculations and round them only at the time of saving them in the output lists.
Example: An example interaction is:
>>> mn,mx,avg,std,cor = main('sample_student_marks.csv')
The output returned in the variables are:
>>> mn
[0.0, 6.0, 3.0, 5.0, 1.0, 7.0, 9.0, 2.0, 262.0]
>>> mx
[98.0, 96.0, 92.0, 92.0, 96.0, 97.0, 94.0, 100.0, 587.0]
>>> avg
[49.7667, 53.2333, 61.7333, 54.6333, 57.2333, 55.0, 50.5, 43.0, 425.1]
>>> std
[31.3706, 24.5678, 25.737, 26.1731, 31.6014, 27.3496, 23.8841, 30.7864, 83.7661]
>>> cor
[0.2654, 0.2908, 0.3286, 0.3428, 0.4051, 0.2863, 0.4309, 0.495, 1.0]
NOTE: THIS PROJECT WAS PART OF THE COMPUTATIONAL THINKING WITH PYTHON UNIT (CITS1401) AT THE UNIVERSITY OF WESTERN AUSTRALIA.