Summary  
This chapter demonstrates how to implement code that computes the mean of a dataset, sums the squared deviations to calculate variance, and then derives the standard deviation by taking the square root of that variance.

General domain of usage  
Data analysis

import unittest
import pandas as pd

def _dynamic_test(test_case, condition, success_msg, failure_msg):
    if condition:
        test_case._testMethodName = success_msg
        test_case.assertTrue(True, success_msg)
    else:
        test_case._testMethodName = failure_msg
        test_case.fail(failure_msg)

class TestVarianceStd(unittest.TestCase):
    def test_variance_std(self):
        # ÐÐ¼Ð¿Ð¾ÑÑ ÐºÐ¾ÑÐ¸ÑÑÑÐ²Ð°ÑÑÐºÐ¾Ð³Ð¾ ÑÑÑÐµÐ½Ð½Ñ
        import user_code

        # ÐÐ°Ð²Ð°Ð½ÑÐ°Ð¶ÑÑÐ¼Ð¾ ÑÑ ÑÐ°Ð¼Ñ Ð´Ð°Ð½Ñ
        df = pd.read_csv(
            'https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a849660e-ddfa-4033-80a6-94a1b7772e23/update/ds_salaries_statistics',
            index_col=0
        )

        # ÐÐ±ÑÐ¸ÑÐ»ÑÑÐ¼Ð¾ Ð¾ÑÑÐºÑÐ²Ð°Ð½Ñ Ð·Ð½Ð°ÑÐµÐ½Ð½Ñ
        expected_var = df['salary'].var()
        expected_std = df['salary'].std()

        # ÐÐµÑÐµÐ²ÑÑÑÑÐ¼Ð¾ Ð· ÑÐ¾ÑÐ½ÑÑÑÑ Ð´Ð¾ 1e-6
        condition = (
            abs(user_code.var - expected_var) < 1e-6 and
            abs(user_code.std - expected_std) < 1e-6
        )

        _dynamic_test(
            self,
            condition,
            "The variance and standard deviation are calculated correctly.",
            "The variance and/or standard deviation are incorrect. Check your calculations."
        )

if __name__ == "__main__":
    unittest.main()


test_code.py

Pythonを用いたデータ分析で使用される主要な統計概念を学習します。本コースでは、平均、中央値、最頻値、分散、標準偏差などの記述統計に加え、サンプリング、確率分布、中心極限定理、外れ値検出についても取り上げます。

分散と標準偏差の計算

解答