Easy grading provides the code required for calculating chilean grades from a score dataframe. It also provides an automatic graphical representation of them with the minimum summary statistics required for test analysis.
Chilean grades calculation is not as straight forward as one might think. Easy_grading helps solving the task with an user-friendly code that helps educators obtain grades and the respective analysis in a rapid manner.
The sample_data_generator.py generates a sample dataframe (sample_score_data.csv) that can be used for grade calculation and representation. Contains four columns 1) Student, represents 100 course students; 2) Score Random, represents the score obtained by each student from pseudo-random number between 0 and 100 points; 3) Score Normal, represents the score obtained by each student from a Normal distribution of mean 60 and standard deviation 10; 4) Score Gamma, represents the score obtained by each student from a Gamma distribution of alpha 2 and beta 2 with a maximum score of 20.
The Easy_grading.py takes a score csv dataframe as input and asks for the maximum score of a test and the score percentage for approval. Then it calculates the grades for the desired columns and outputs the original dataframe with the grades' columns appended.
In the terminal run:
python3 Easy_grading.py <score_csv_dataframe.csv>
Then follow the instructions for the different inputs asked.
Feel free to optimize/modify the code to have better or different results.
MIT