Documentation can be found on : https://github.com/viktoriussuwandi/Mean-Variance-Standard-Deviation-Calculator
This is the complete Mean-Variance-Standard Deviation Calculator project. Instructions for building the project can be found at https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with-python-projects/mean-variance-standard-deviation-calculator
* split into different detail functions
Create a function named calculate() in mean_var_std.py that uses Numpy to output the mean, variance, standard deviation, max, min, and sum of the rows, columns, and elements in a 3 x 3 matrix.
The input of the function should be a list containing 9 digits. The function should convert the list into a 3 x 3 Numpy array, and then return a dictionary containing the mean, variance, standard deviation, max, min, and sum along both axes and for the flattened matrix.
The returned dictionary should follow this format:
If a list containing less than 9 elements is passed into the function, it should raise a ValueError exception with the message: "List must contain nine numbers." The values in the returned dictionary should be lists and not Numpy arrays.
For example, calculate([0,1,2,3,4,5,6,7,8]) should return:
The unit tests for this project are in test_module.py.
For development, you can use main.py to test your calculate() function. Click the "run" button and main.py will run.
We imported the tests from test_module.py to main.py for your convenience. The tests will run automatically whenever you hit the "run" button.
