{"id":11600,"date":"2017-07-27T12:00:11","date_gmt":"2017-07-27T03:00:11","guid":{"rendered":"http:\/\/sitest.jp\/blog\/?p=11600"},"modified":"2017-07-26T20:25:30","modified_gmt":"2017-07-26T11:25:30","slug":"python%e3%81%a7%e7%b5%b1%e8%a8%88%e5%ad%a6%e5%85%a5%e9%96%80%e2%80%95%e5%81%8f%e5%b7%ae%e5%80%a4%e3%81%a8%e3%81%af%ef%bc%9fpython%e3%81%a7%e8%a8%88%e7%ae%97%e3%81%97%e3%81%a6%e3%81%bf%e3%82%88","status":"publish","type":"post","link":"https:\/\/sitest.jp\/blog\/?p=11600","title":{"rendered":"Python\u3067\u7d71\u8a08\u5b66\u5165\u9580\u2015\u504f\u5dee\u5024\u3068\u306f\uff1fPython\u3067\u8a08\u7b97\u3057\u3066\u307f\u3088\u3046\u2015"},"content":{"rendered":"

\u7d71\u8a08\u5b66\u306e\u8003\u3048\u65b9\u3068\u3057\u3066\u300c\u5e73\u5747\u300d\u306e\u6b21\u304f\u3089\u3044\u306b\u99b4\u67d3\u307f\u6df1\u304f\u3001\u304b\u3064\u3088\u304f\u308f\u304b\u3089\u306a\u3044\u3082\u306e\u306b\u30c6\u30b9\u30c8\u306e\u6210\u7e3e\u3067\u304a\u306a\u3058\u307f\u306e\u300c\u504f\u5dee\u5024\u300d\u304c\u3042\u308a\u307e\u3059\u3002\u4eca\u56de\u306f Python (3\u7cfb)\u3092\u4f7f\u3063\u3066\u3001\u504f\u5dee\u5024\u3092\u6c42\u3081\u3066\u307f\u307e\u3059\u3002<\/p>\n

<\/p>\n

\n

\n\u504f\u5dee\u5024\u3068\u306f\u306a\u3093\u3060\u308d\u3046\uff1f\u2015\u504f\u5dee\u5024\u306f100\u70b9\u6e80\u70b9\u3068\u306f\u5168\u7136\u95a2\u4fc2\u306a\u3044
\n<\/h3>\n<\/div>\n

\u504f\u5dee\u5024\u3068\u306f\u300c\u305d\u306e\u96c6\u56e3\u306e\u4e2d\u306e\u5e73\u5747\u3092\u3069\u308c\u304f\u3089\u3044\u4e0a\u56de\u3063\u3066\u3044\u308b\u304b(\u4e0b\u56de\u3063\u3066\u3044\u308b\u304b)\u3092\u793a\u3057\u305f\u5024\u300d\u3067\u3059\u3002\u504f\u5dee\u5024\u3068\u3057\u3066\u3088\u304f\u898b\u304b\u3051\u308b\u5024\u304c\u5927\u4f5330\u301c70\u304f\u3089\u3044\u306a\u306e\u3067\u3001100\u70b9\u6e80\u70b9\u306e\u30c6\u30b9\u30c8\u306e\u70b9\u6570\u3068\u5927\u304d\u306a\u95a2\u9023\u304c\u3042\u308a\u305d\u3046\u3067\u3059\u304c\u3001\u305d\u3046\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/p>\n

\u4f8b\u3048\u30701000\u70b9\u6e80\u70b9\u3067\u3001\u5e73\u5747\u70b9\u304c500\u70b9\u3067\u3042\u3063\u3066\u3082\u6975\u7aef\u306b\u3067\u304d\u308b\u3072\u3068\u3084\u3001\u3067\u304d\u306a\u3044\u3072\u3068\u304c\u6570\u591a\u304f\u3044\u306a\u3044\u9650\u308a\u3001\u504f\u5dee\u5024\u306f\u304a\u3088\u305d30\u301c70\u304f\u3089\u3044\u304c\u3088\u304f\u307f\u3089\u308c\u308b\u5024\u3068\u306a\u308a\u307e\u3059\u3002<\/p>\n

\u300c100\u70b9\u6e80\u70b9\u306e\u30c6\u30b9\u30c8\u300d\u304b\u3089\u96e2\u308c\u3066\u8003\u3048\u308b\u305f\u3081\u306b\u3001\u504f\u5dee\u5024\u3092\u3061\u3087\u3063\u3068\u9055\u3046\u6570\u5b57\u3067\u8868\u73fe\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n

\u504f\u5dee\u5024\u306b\u304a\u3044\u3066\u57fa\u6e96\u3068\u306a\u308b\u5024\u306f50\u3067\u3059\u304c\u3001\u3053\u308c\u306b\u306f\u5fc5\u7136\u6027\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u3067\u3059\u306e\u3067\u3001\u8a66\u3057\u306b\u57fa\u6e96\u3068\u306a\u308b\u5024\u30920\u306b\u3057\u3066\u307f\u307e\u3059\u3002\u3059\u308b\u3068\u57fa\u6e96\u304c\u305a\u308c\u308b\u306e\u3067\u504f\u5dee\u502440\u306f\u3001\u300c-10\u300d\u3002\u504f\u5dee\u502465\u306f\u300c+15\u300d\u3068\u306a\u308a\u307e\u3059\u3002<\/p>\n

\u3055\u3089\u306b1\u301c30\u304f\u3089\u3044\u306e\u6570\u3067\u30d7\u30e9\u30b9\u30fb\u30de\u30a4\u30ca\u30b9\u3059\u308b\u5fc5\u8981\u3082\u306a\u3044\u306e\u3067\u601d\u3044\u5207\u3063\u3066\u6570\u5b57\u30921\/10\u306b\u3057\u3066\u3001\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u3068\u547c\u3093\u3067\u307f\u307e\u3059(\u3053\u306e\u8a18\u4e8b\u4ee5\u5916\u3067\u306f\u901a\u7528\u3057\u306a\u3044\u547c\u3073\u65b9\u3067\u3059)\u3002\u504f\u5dee\u502440\u306f\u3001\u300c-1\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u300d\u3002\u504f\u5dee\u502465\u306f\u300c+1.5\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u300d\u3068\u306a\u308a\u307e\u3059\u3002<\/p>\n

\u3067\u306f\u3001\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u304c\u300c1\u30dd\u30a4\u30f3\u30c8\u5897\u3048\u308b(\u666e\u901a\u306e\u504f\u5dee\u5024\u3067\u3044\u3046\u306810\u5897\u3048\u308b)\u300d\u3068\u5177\u4f53\u7684\u306b\u30c6\u30b9\u30c8\u306e\u70b9\u6570\u306f\u4f55\u70b9\u5897\u3048\u308b\u306e\u3067\u3057\u3087\u3046\u304b\uff1f\u3042\u308b\u3044\u306f1\u30dd\u30a4\u30f3\u30c8\u6e1b\u308b\u3068\u5177\u4f53\u7684\u306b\u4f55\u70b9\u6e1b\u308b\u306e\u3067\u3057\u3087\u3046\u304b\uff1f\u8a00\u3044\u63db\u3048\u308c\u3070\u30011\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u306b\u306f\u5b9f\u969b\u306e\u30c6\u30b9\u30c8\u306b\u304a\u3051\u308b\u4f55\u70b9\u5206\u306e\u4fa1\u5024\u304c\u3042\u308b\u306e\u3067\u3057\u3087\u3046\u304b\uff1f<\/p>\n

\u3053\u306e\u5024\u3092\u6c42\u3081\u308b\u3053\u3068\u304c\u504f\u5dee\u5024\u306e\u8a08\u7b97\u306e\u307b\u307c\u3059\u3079\u3066\u3068\u3044\u3063\u3066\u3082\u8a00\u3044\u904e\u304e\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u3053\u306e1\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u306e\u3053\u3068\u3092\u3001\u3061\u3083\u3093\u3068\u3057\u305f\u7d71\u8a08\u5b66\u306e\u8a00\u8449\u3067\u306f\u300c\u6a19\u6e96\u504f\u5dee\u300d\u3068\u3044\u3044\u307e\u3059\u3002<\/p>\n

\n

\n\u30b0\u30e9\u30d5\u3092\u4f5c\u3063\u3066\u30c7\u30fc\u30bf\u306e\u5168\u4f53\u50cf\u3092\u307f\u3066\u307f\u308b
\n<\/h3>\n<\/div>\n

\u3067\u306f\u3001Python \u3092\u3064\u304b\u3063\u3066\u3001\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u30c6\u30b9\u30c8\u6210\u7e3e\u304b\u3089\u300c\u6a19\u6e96\u504f\u5dee\u300d\u3092\u6c42\u3081\u3001\u6700\u5f8c\u306bA\u3055\u3093(51\u70b9)\u306e\u504f\u5dee\u5024\u3092\u6c42\u3081\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n

\u6a19\u6e96\u504f\u5dee\u3092\u6c42\u3081\u308b\u306b\u306f\u3001\u5b66\u5e74\u5168\u54e1\u306e\u30c6\u30b9\u30c8\u306e\u70b9\u6570\u3092\u77e5\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\uff08\u4e00\u90e8\u3060\u3051\u3092\u62bd\u51fa\u3059\u308b\u3084\u308a\u65b9\u3082\u3042\u308a\u307e\u3059\u304c\u3001100\u4eba\u7a0b\u5ea6\u3067\u3057\u305f\u3089\u3001\u5168\u54e1\u5206\u306e\u70b9\u6570\u3067\u8a08\u7b97\u3057\u305f\u307b\u3046\u304c\u3088\u3044\u3067\u3057\u3087\u3046\uff09\u3002<\/p>\n

\u307e\u305a\u3001\u4eca\u56de\u4f7f\u3046\u30c6\u30b9\u30c8\u306e\u70b9\u6570\u3092\u914d\u5217\u3067\u8868\u3057\u3066\u307f\u307e\u3059\u3002A\u3055\u3093\u306e\u5b66\u5e74\u306f100\u4eba\u3044\u308b\u306e\u3067\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u611f\u3058\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n

scores = [62, 75, 82, 43, 81, 71, 56, 49, 54, 14, 79, 64, 76, 81, 51, 70, 82, 88, 62, 66, 100, 45, 53, 63, 60, 72, 90, 72, 22, 74, 55, 77, 100, 36, 54, 79, 64, 70, 84, 65, 47, 58, 32, 81, 77, 38, 71, 26, 68, 41, 44, 54, 67, 45, 34, 48, 51, 44, 89, 25, 98, 99, 39, 56, 57, 55, 57, 46, 56, 45, 55, 73, 29, 63, 68, 28, 45, 78, 70, 93, 36, 61, 52, 77, 81, 70, 55, 65, 82, 56, 76, 39, 61, 75, 66, 72, 55, 50, 56]\n<\/code><\/pre>\n
\u3053\u308c\u3060\u3068\u3088\u304f\u308f\u304b\u3089\u306a\u3044\u306e\u3067\u3001\u3061\u3087\u3063\u3068\u6a2a\u9053\u306b\u305d\u308c\u3066\u3001\u3060\u3044\u305f\u3044\u3069\u308c\u304f\u3089\u3044\u306e\u70b9\u6570\u306e\u751f\u5f92\u304c\u591a\u3044\u306e\u304b\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3068\u3044\u3046\u30b0\u30e9\u30d5\u306b\u3057\u3066\u307f\u307e\u3059\u3002<\/p>\n
\u504f\u5dee\u5024\u3092\u3082\u3068\u3081\u308b\u3053\u3068\u304c\u30c6\u30fc\u30de\u306a\u306e\u3067\u8aac\u660e\u306f\u7701\u304d\u307e\u3059\u304c\u3001matplotlib \u3068\u3044\u3046\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3046\u3068\u30c7\u30fc\u30bf\u304b\u3089\u30b0\u30e9\u30d5\u3092\u7c21\u5358\u306b\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n
import matplotlib.pyplot as plt\nimport numpy as np\nimport matplotlib as mpl\nmpl.rcParams['font.family'] = 'Kozuka Gothic Pr6N'\n\nnp_scores = np.array(scores)\nplt.hist(np_scores)\nplt.title('\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u70b9\u6570(\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0)')\nplt.xlabel('\u70b9\u6570')\nplt.ylabel('\u4eba\u6570')\nplt.xticks( np.arange(0, 110, 5) )\nplt.yticks( np.arange(0, 20, 2) )\nplt.show()\n<\/code><\/pre>\n
\"\"<\/p>\n
50\u70b9\u524d\u5f8c\u306e\u751f\u5f92\u304c\u4e00\u756a\u591a\u304f\u3001\u6b21\u306b\u591a\u3044\u306e\u304c\u300180\u70b9\u524d\u5f8c\u306e\u751f\u5f92\u3067\u3059\u3002\u5927\u4f53\u3053\u306e\u9593\u306b\u307b\u3068\u3093\u3069\u306e\u751f\u5f92\u304c\u4f4d\u7f6e\u3059\u308b\u3088\u3046\u3067\u3059\u3002\u9006\u306b0\u70b9\u3084\u4e00\u6841\u306e\u70b9\u6570\u306e\u751f\u5f92\u306f\u3044\u306a\u3044\u3088\u3046\u3067\u3059\u306d\u3002<\/p>\n
\n
\n\u5e73\u5747\u70b9\u3068\u6a19\u6e96\u504f\u5dee\u3092Numpy\u3067\u6c42\u3081\u308b
\n<\/h3>\n<\/div>\n
\u3067\u306f\u3001\u300c\u6a19\u6e96\u504f\u5dee\u300d\u3092 Python \u3067\u6c42\u3081\u308b\u306b\u3042\u305f\u308a\u3001\u307e\u305a\u306f\u5e73\u5747\u70b9\u3092\u6c42\u3081\u3066\u307f\u307e\u3057\u3087\u3046<\/p>\n
\u30b0\u30e9\u30d5\u3092\u4f5c\u308b\u3068\u304d\u306b\u3059\u3067\u306b\u4f7f\u3063\u3066\u3057\u307e\u3063\u305f\u306e\u3067\u3059\u304c\u3001\u7d71\u8a08\u95a2\u4fc2\u306e\u8a08\u7b97\u306f\u3000Numpy\u3000\u3068\u3044\u3046\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3046\u3068\u7c21\u5358\u306b\u3067\u304d\u307e\u3059\u3002\u69d8\u3005\u306a\u3000Python \u74b0\u5883\u306b\u4ed8\u3044\u3066\u304f\u308b\u306e\u3067\u3001\u3082\u3046\u5165\u3063\u3066\u3044\u308b\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u304c\u3001\u306a\u3044\u5834\u5408\u306f\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n
pip install numpy\n<\/code><\/pre>\n
\u5e73\u5747\u70b9\u3092\u6c42\u3081\u308b\u30bd\u30fc\u30b9\u306f\u4ee5\u4e0b\u3067\u3059\u3002\u7c21\u5358\u3067\u3059\u306d\uff01<\/p>\n
import numpy as np\n\nscores = [62, 75, 82, 43, 81, 71, 56, 49, 54, 14, 79, 64, 76, 81, 51, 70, 82, 88, 62, 66, 100, 45, 53, 63, 60, 72, 90, 72, 22, 74, 55, 77, 100, 36, 54, 79, 64, 70, 84, 65, 47, 58, 32, 81, 77, 38, 71, 26, 68, 41, 44, 54, 67, 45, 34, 48, 51, 44, 89, 25, 98, 99, 39, 56, 57, 55, 57, 46, 56, 45, 55, 73, 29, 63, 68, 28, 45, 78, 70, 93, 36, 61, 52, 77, 81, 70, 55, 65, 82, 56, 76, 39, 61, 75, 66, 72, 55, 50, 56]\n\n#\u901a\u5e38\u306e\u914d\u5217\u3092\u3088\u308a\u9ad8\u6027\u80fd\u306aNumpy\u914d\u5217\u306b\u5909\u63db\u3057\u307e\u3059\u3002\nnp_scores = np.array(scores)\n\n#numpy.mean \u30e1\u30bd\u30c3\u30c9\u3060\u3051\u3067\u7b97\u8853\u5e73\u5747(\u3044\u308f\u3086\u308b\u5e73\u5747)\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002\nmean = np.mean(np_scores)\n\nprint(\u201c\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u5e73\u5747\u70b9:\"+str(mean))\n<\/code><\/pre>\n
\u51fa\u529b\u306f\u4ee5\u4e0b\u3067\u3059<\/p>\n
\u3068\u3042\u308b\u30af\u30e9\u30b9\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u5e73\u5747\u70b9:61.3737373737\n<\/code><\/pre>\n
\u9ad8\u3081\u306e\u5e73\u5747\u70b9\u3067\u3059\u306d\u3002
\n\u3055\u3089\u306b\u6a19\u6e96\u504f\u5dee\u3092\u6c42\u3081\u3066\u307f\u307e\u3059\u3002\u5b9f\u306f\u3000Numpy\u3000\u3092\u3064\u304b\u3048\u3070\u3001\u5b9f\u8cea1\u884c\u3067\u6c42\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
#Numpy\u914d\u5217\u306b\u5909\u63db\u3059\u308b\u30b3\u30fc\u30c9\u306f\u7701\u7565\u3057\u307e\u3059\n\n#numpy.std \u30e1\u30bd\u30c3\u30c9\u3060\u3051\u3067\u6a19\u6e96\u504f\u5dee\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002\nstd = np.std(np_scores)\n\nprint(\"\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u6a19\u6e96\u504f\u5dee:\"+str(std))\n<\/code><\/pre>\n
\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u6a19\u6e96\u504f\u5dee:18.3576069932\n<\/code><\/pre>\n
\u3068\u3044\u3046\u308f\u3051\u3067\u3001\u3053\u306e\u5b66\u5e74\u306e\u3053\u306e\u56fd\u8a9e\u306e\u30c6\u30b9\u30c8\u3067\u306f\u3001\u300c\u6a19\u6e96\u504f\u5dee\u300d\u3001\u3059\u306a\u308f\u30611\u504f\u5dee\u30dd\u30a4\u30f3\u30c8\u304c\u7d0418\u70b9\u306e\u4fa1\u5024\u3092\u6301\u3063\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3057\u305f\u3002\u5e73\u5747\u70b9\u304c\u7d0461\u70b9\u306a\u306e\u3067\u300161\u70b9\u3092\u53d6\u308c\u30700\u504f\u5dee\u30dd\u30a4\u30f3\u30c8(\u504f\u5dee\u502450)\u3067\u3059\u3002<\/p>\n
+1\u504f\u5dee\u30dd\u30a4\u30f3\u30c8(\u504f\u5dee\u502460)\u306a\u3089 61 + 18 = 79 \u306a\u306e\u3067\u7d0479\u70b9\u3001-0.5\u504f\u5dee\u30dd\u30a4\u30f3\u30c8(\u504f\u5dee\u502445)\u306a\u3089 61- (18 \u00f7 2) = 52\u3067\u7d0452\u70b9 \u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/p>\n
\n
\n\u3044\u3088\u3044\u3088\u3001Python\u3067\u504f\u5dee\u5024\u3092\u3082\u3068\u3081\u307e\u3059
\n<\/h3>\n<\/div>\n
\u3067\u306f\u3001\u3044\u3088\u3044\u3088A\u3055\u3093(51\u70b9)\u306e\u504f\u5dee\u5024\u3092 Python\u3067\u6c42\u3081\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u504f\u5dee\u5024\u3092\u6c42\u3081\u308b\u306b\u306f\u3001\u3059\u3067\u306b\u6c42\u3081\u305f\u5e73\u5747\u3068\u6a19\u6e96\u504f\u5dee\u3001\u305d\u3057\u3066\u5f97\u70b9\u3092\u504f\u5dee\u5024\u306e\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306b\u5f53\u3066\u306f\u3081\u308b\u3060\u3051\u3067\u3059\u3002
\n\u4ee5\u4e0b\u304c\u5b8c\u6210\u7248\u306e\u30b3\u30fc\u30c9\u3067\u3059\u3002<\/p>\n
import numpy as np\n\nscores = [62, 75, 82, 43, 81, 71, 56, 49, 54, 14, 79, 64, 76, 81, 51, 70, 82, 88, 62, 66, 100, 45, 53, 63, 60, 72, 90, 72, 22, 74, 55, 77, 100, 36, 54, 79, 64, 70, 84, 65, 47, 58, 32, 81, 77, 38, 71, 26, 68, 41, 44, 54, 67, 45, 34, 48, 51, 44, 89, 25, 98, 99, 39, 56, 57, 55, 57, 46, 56, 45, 55, 73, 29, 63, 68, 28, 45, 78, 70, 93, 36, 61, 52, 77, 81, 70, 55, 65, 82, 56, 76, 39, 61, 75, 66, 72, 55, 50, 56]\n\n#\u901a\u5e38\u306e\u914d\u5217\u3092\u3088\u308a\u9ad8\u6027\u80fd\u306aNumpy\u914d\u5217\u306b\u5909\u63db\u3057\u307e\u3059\u3002\nnp_scores = np.array(scores)\n\n#numpy.mean \u30e1\u30bd\u30c3\u30c9\u3060\u3051\u3067\u7b97\u8853\u5e73\u5747(\u3044\u308f\u3086\u308b\u5e73\u5747)\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002\nmean = np.mean(np_scores)\nprint(\"\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u5e73\u5747\u70b9:\"+str(mean))\n\n#numpy.std \u30e1\u30bd\u30c3\u30c9\u3060\u3051\u3067\u6a19\u6e96\u504f\u5dee\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002\nstd = np.std(np_scores)\nprint(\"\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u6a19\u6e96\u504f\u5dee:\"+str(std))\n\n#A\u3055\u3093\u306e\u5f97\u70b9\nscore_a = 51\n\n#A\u3055\u3093\u306e\u5f97\u70b9\u3001\u5b66\u5e74\u306e\u5e73\u5747\u3068\u6a19\u6e96\u504f\u5dee\u3092\u504f\u5dee\u5024\u306e\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306b\u5f53\u3066\u306f\u3081\u3066\u8a08\u7b97\u3057\u307e\u3059\u3002\n#(\u5f97\u70b9 - \u5e73\u5747\u70b9) \/ \u6a19\u6e96\u504f\u5dee  \u3067A\u3055\u3093\u306e\u300c\u5e73\u5747\u3068\u6bd4\u3079\u3066\u6a19\u6e96\u504f\u5dee\u3044\u304f\u3064\u5206\u306e\u5dee\u304c\u3042\u308b\u304b\u300d\u304c\u6c42\u307e\u308a\u307e\u3059\u3002\ndeviation = (score_a - mean) \/ std\n\n#\u305d\u306e\u5024\u309210\u500d\u3057\u300150\u3092\u8db3\u3059\u3068\u300c\u504f\u5dee\u5024\u300d\u306b\u306a\u308a\u307e\u3059\u3002\u672c\u6587\u3067\u3082\u8ff0\u3079\u305f\u3088\u3046\u306b\u3001\n#\u3053\u308c\u306b\u306f\u300c\u308f\u304b\u308a\u3084\u3059\u304f\u3059\u308b\u305f\u3081\u300d\u4ee5\u5916\u306e\u5fc5\u7136\u6027\u306f\u3042\u308a\u307e\u305b\u3093\u3002\ndeviation_value = 50 + deviation * 10\n\nprint(\"A\u3055\u3093\u306e\u56fd\u8a9e\u306e\u70b9\u6570:\"+str(51))\nprint(\"A\u3055\u3093\u306e\u56fd\u8a9e\u306e\u504f\u5dee\u5024:\"+str(deviation_value))\n\n<\/code><\/pre>\n
\u51fa\u529b\u7d50\u679c<\/p>\n
\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u5e73\u5747\u70b9:61.3737373737\n\u3068\u3042\u308b\u5b66\u5e74\u306e\u56fd\u8a9e\u306e\u6a19\u6e96\u504f\u5dee:18.3576069932\nA\u3055\u3093\u306e\u56fd\u8a9e\u306e\u70b9\u6570:51\nA\u3055\u3093\u306e\u56fd\u8a9e\u306e\u504f\u5dee\u5024:44.3490797152\n<\/code><\/pre>\n
\u3055\u3066\u3001A\u3055\u3093\u306e\u504f\u5dee\u5024\u304c\u6c42\u307e\u308a\u307e\u3057\u305f\u300251\u70b9\u53d6\u3063\u3066\u3044\u308b\u306e\u306b\u5168\u4f53\u306e\u5e73\u5747\u70b9\u304c\u9ad8\u3044\u305f\u3081\u3001\u771f\u3093\u4e2d\u3092\u6307\u305950\u3088\u308a\u3082\u4f4e\u304f\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n
\u4eca\u56de\u3001\u3044\u3061\u3070\u3093\u5927\u4e8b\u306a\u300c\u6a19\u6e96\u504f\u5dee\u300d\u306e\u610f\u5473\u3084\u6c42\u3081\u65b9\u306b\u3064\u3044\u3066\u306f Python(Numpy) \u4efb\u305b\u306b\u3057\u3066\u3057\u307e\u3044\u307e\u3057\u305f\u3002\u304d\u3061\u3093\u3068\u77e5\u308a\u305f\u3044\u5834\u5408\u306f\u3001\u7d71\u8a08\u5b66\u306e\u672c\u3092\u8aad\u3080\u306e\u3092\u304a\u3059\u3059\u3081\u3057\u307e\u3059\u3002\u4e0b\u8a18\u306e\u672c\u304c\u308f\u304b\u308a\u3084\u3059\u304b\u3063\u305f\u3067\u3059\u3002<\/p>\n
\u30de\u30f3\u30ac\u3067\u308f\u304b\u308b\u7d71\u8a08\u5b66<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u7d71\u8a08\u5b66\u306e\u8003\u3048\u65b9\u3068\u3057\u3066\u300c\u5e73\u5747\u300d\u306e\u6b21\u304f\u3089\u3044\u306b\u99b4\u67d3\u307f\u6df1\u304f\u3001\u304b\u3064\u3088\u304f\u308f\u304b\u3089\u306a\u3044\u3082\u306e\u306b\u30c6\u30b9\u30c8\u306e\u6210\u7e3e\u3067\u304a\u306a\u3058\u307f\u306e\u300c\u504f\u5dee\u5024\u300d\u304c\u3042\u308a\u307e\u3059\u3002\u4eca\u56de\u306f Python (3\u7cfb)\u3092\u4f7f\u3063\u3066\u3001\u504f\u5dee\u5024\u3092\u6c42\u3081\u3066\u307f\u307e\u3059\u3002<\/p>\n","protected":false},"author":1,"featured_media":11637,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[27,47],"tags":[],"acf":false,"_links":{"self":[{"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/posts\/11600"}],"collection":[{"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/comments?post=11600"}],"version-history":[{"count":12,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/posts\/11600\/revisions"}],"predecessor-version":[{"id":12109,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/posts\/11600\/revisions\/12109"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/media\/11637"}],"wp:attachment":[{"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/media?parent=11600"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/categories?post=11600"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sitest.jp\/blog\/wp-json\/wp\/v2\/tags?post=11600"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}