Data Analysis with Python Projects - Mean-Variance-Standard Deviation Calculator

Python
1

Tell us what’s happening:
Describe your issue in detail here.

So I managed to work on this project but for some reason that I can’t figure out, my code won’t pass the 2nd test.

Your code so far

boilerplate-mean-variance-standard-deviation-calculator (1) - Replit

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Challenge: Data Analysis with Python Projects - Mean-Variance-Standard Deviation Calculator

Link to the challenge:

2

Do you happen to have the error messages you’re receiving. They should state exactly what it doesn’t like. It may say something like 3.2838 is not equal to 3.2888 which indicates where the problem lies.

Sometimes something as little as number of decimal places can cause an issue. I do have to say you wrote a lot of code :slight_smile: I’ll explain why that is funny after pass.

3

Hi @AngbandShadow5! I copied and ran your code and found 1 error in the result for variance (one number was SLIGHTLY off) and 1 error in the result for standard deviation (one number was slightly off).

If you go into test_module.py, you can see the three test cases and look into the desired answer for test case 2 and see where you went wrong. To visualize the test case 2 results for yourself then just go into the test_module.py folder and test case 2 (test_calculate2) will show you the input given to the function for that test case and then you can copy the input and paste it into the main.py folder to run test case 2 and see the output.

This should help you to at least spot where the issue is occurring.

I hope that this helps! If you have any more questions please feel free to ask!

4

The expected return value of the test you are failing is:

{
    'mean': [
        [4.666666666666667, 4.333333333333333, 2.6666666666666665],
        [5.0, 3.0, 3.6666666666666665], 3.888888888888889
    ],
    'variance': [
        [9.555555555555555, 11.555555555555557, 4.222222222222222],
        [10.666666666666666, 0.0, 14.888888888888891], 9.209876543209875
    ],
    'standard deviation': [
        [3.0912061651652345, 3.39934634239519, 2.0548046676563256],
        [3.265986323710904, 0.0, 3.8586123009300755], 3.0347778408328137
    ],
    'max': [
        [9, 9, 5],
        [9, 3, 9], 9
    ],
    'min': [
        [2, 1, 0],
        [1, 3, 0], 0
    ],
    'sum': [
        [14, 13, 8],
        [15, 9, 11], 35
    ]
}

You are returning:

{
    'mean': [
        [4.666666666666667, 4.333333333333333, 2.6666666666666665],
        [5.0, 3.0, 3.6666666666666665], 3.888888888888889
    ],
    'variance': [
        [9.555555555555555, 11.555555555555557, 4.222222222222222],
        [10.666666666666666, 0.0, 14.888888888888891], 9.209876543209877
    ],
    'standard deviation': [
        [3.0912061651652345, 3.39934634239519, 2.0548046676563256],
        [3.265986323710904, 0.0, 3.8586123009300755], 3.034777840832814
    ],
    'max': [
        [9, 9, 5],
        [9, 3, 9], 9
    ],
    'min': [
        [2, 1, 0],
        [1, 3, 0], 0
    ],
    'sum': [
        [14, 13, 8],
        [15, 9, 11], 35
    ]
}
5

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