開発環境
- macOS High Sierra - Apple
- Emacs (Text Editor)
- Python 3.6 (プログラミング言語)
Pythonからはじめる数学入門 (Amit Saha (著)、黒川 利明 (翻訳)、オライリージャパン)の2章(データを統計量で記述する)、3.9(プログラミングチャレンジ)、問題3-3(他のCSVデータでの実験)を取り組んでみる。
コード(Emacs)
Python 3
#!/usr/bin/env python3 from collections import Counter import csv import matplotlib.pyplot as plt def read_csv(filename): with open(filename) as f: reader = csv.reader(f) next(reader) years = [] pops = [] for row in reader: years.append(row[0].split('-')[0]) pops.append(float(row[1])) years.reverse() pops.reverse() return years, pops def read_nums(filename): with open(filename) as f: nums = [float(line) for line in f] return nums def mean(nums): s = sum(nums) n = len(nums) return s / n def median(nums): n = len(nums) nums.sort() if n % 2 == 0: m1 = n / 2 m2 = n / 2 + 1 m1 = int(m1) - 1 m2 = int(m2) - 1 return (nums[m1] + nums[m2]) / 2 m = (n + 1) / 2 m = int(m) - 1 return nums[m] def mode(nums): c = Counter(nums) nums_freq = c.most_common() max_count = nums_freq[0][1] modes = [num[0] for num in nums_freq if num[1] == max_count] return modes def differences(nums): m = mean(nums) diff = [n - m for n in nums] return diff def variance(nums): diff = differences(nums) squared_diff = [d ** 2 for d in diff] sum_sqaured_diff = sum(squared_diff) return sum_sqaured_diff / len(nums) def standard_deviation(nums): return variance(nums) ** (1 / 2) if __name__ == '__main__': filename = 'USA_SP_POP_TOTL.csv' years, pops = read_csv(filename) xlabels = [f'{years[i]}-{years[i+1]}' for i in range(len(years) - 1)] diff = [pops[i + 1] - pops[i] for i in range(len(pops) - 1)] plt.plot(xlabels, diff) plt.xlabel('Year') plt.ylabel('Population') plt.xticks(range(0, len(years) - 1), rotation=20) plt.savefig('sample3.svg') funcs = [mean, median, mode, variance, standard_deviation] for func in funcs: print(f'{func.__name__.replace("_", " ")}: {func(diff)}')
入出力結果(Terminal, Jupyter(IPython))
$ ./sample3.py mean: 2562366.153846154 median: 2476370.0 mode: [1945000.0, 1971000.0, 1994000.0, 2013000.0, 2033000.0, 2062000.0, 2099000.0, 2119000.0, 2128000.0, 2152000.0, 2156000.0, 2170000.0, 2198000.0, 2204000.0, 2209000.0, 2210000.0, 2235000.0, 2241000.0, 2257000.0, 2261591.0, 2320000.0, 2326224.0, 2346000.0, 2375000.0, 2414000.0, 2470000.0, 2482740.0, 2554696.0, 2609000.0, 2647000.0, 2656238.0, 2677563.0, 2697365.0, 2704000.0, 2711301.0, 2804000.0, 2806544.0, 2847000.0, 2851295.0, 2862759.0, 2863313.0, 3020000.0, 3116000.0, 3122411.0, 3152000.0, 3186000.0, 3197000.0, 3207000.0, 3263000.0, 3358000.0, 3405000.0, 3533000.0] variance: 188985554755.28406 standard deviation: 434724.6884584358 $
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