├── .gitignore
├── requirements.txt
├── .vscode
    └── settings.json
├── mean_var_std.py
├── main.py
├── .gitpod.yml
├── README.md
└── test_module.py


/.gitignore:
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1 | __pycache__/
2 | 


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/requirements.txt:
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1 | numpy==1.18.5
2 | 


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/.vscode/settings.json:
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1 | {
2 |   "workbench.colorTheme": "freeCodeCamp Dark Theme"
3 | }
4 | 


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/mean_var_std.py:
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1 | import numpy as np
2 | 
3 | def calculate(list):
4 | 
5 | 
6 | 
7 | 
8 |     return calculations


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/main.py:
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1 | # This entrypoint file to be used in development. Start by reading README.md
2 | import mean_var_std
3 | from unittest import main
4 | 
5 | print(mean_var_std.calculate([0,1,2,3,4,5,6,7,8]))
6 | 
7 | # Run unit tests automatically
8 | main(module='test_module', exit=False)


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/.gitpod.yml:
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1 | image: gitpod/workspace-python-3.8
2 | 
3 | tasks:
4 |   - init: pip install -r requirements.txt
5 | 
6 | vscode:
7 |   extensions:
8 |     - https://github.com/freeCodeCamp/freecodecamp-dark-vscode-theme/releases/download/v1.0.0/freecodecamp-dark-vscode-theme-1.0.0.vsix
9 | 


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/README.md:
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1 | # Mean-Variance-Standard Deviation Calculator
2 | 
3 | This is the boilerplate for the Mean-Variance-Standard Deviation Calculator project. Instructions for building your project can be found at https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with-python-projects/mean-variance-standard-deviation-calculator
4 | 


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/test_module.py:
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 1 | import unittest
 2 | import mean_var_std
 3 | 
 4 | 
 5 | # the test case
 6 | class UnitTests(unittest.TestCase):
 7 |     def test_calculate(self):
 8 |         actual = mean_var_std.calculate([2,6,2,8,4,0,1,5,7])
 9 |         expected = {'mean': [[3.6666666666666665, 5.0, 3.0], [3.3333333333333335, 4.0, 4.333333333333333], 3.888888888888889], 'variance': [[9.555555555555557, 0.6666666666666666, 8.666666666666666], [3.555555555555556, 10.666666666666666, 6.222222222222221], 6.987654320987654], 'standard deviation': [[3.091206165165235, 0.816496580927726, 2.943920288775949], [1.8856180831641267, 3.265986323710904, 2.494438257849294], 2.6434171674156266], 'max': [[8, 6, 7], [6, 8, 7], 8], 'min': [[1, 4, 0], [2, 0, 1], 0], 'sum': [[11, 15, 9], [10, 12, 13], 35]}
10 |         self.assertAlmostEqual(actual, expected, "Expected different output when calling 'calculate()' with '[2,6,2,8,4,0,1,5,7]'")
11 | 
12 |     def test_calculate2(self):
13 |         actual = mean_var_std.calculate([9,1,5,3,3,3,2,9,0])
14 |         expected = {'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]}
15 |         self.assertAlmostEqual(actual, expected, "Expected different output when calling 'calculate()' with '[9,1,5,3,3,3,2,9,0]'")
16 |     
17 |     def test_calculate_with_few_digits(self):
18 |         self.assertRaisesRegex(ValueError, "List must contain nine numbers.", mean_var_std.calculate, [2,6,2,8,4,0,1,])
19 | 
20 | if __name__ == "__main__":
21 |     unittest.main()
22 | 


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