{"id":1654,"date":"2023-07-25T12:06:20","date_gmt":"2023-07-25T12:06:20","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%9e%e3%83%b3%e3%83%8f%e3%83%83%e3%82%bf%e3%83%b3%e3%83%aa%e3%83%a2%e3%83%bc%e3%83%88python\/"},"modified":"2023-07-25T12:06:20","modified_gmt":"2023-07-25T12:06:20","slug":"%e3%83%9e%e3%83%b3%e3%83%8f%e3%83%83%e3%82%bf%e3%83%b3%e3%83%aa%e3%83%a2%e3%83%bc%e3%83%88python","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%9e%e3%83%b3%e3%83%8f%e3%83%83%e3%82%bf%e3%83%b3%e3%83%aa%e3%83%a2%e3%83%bc%e3%83%88python\/","title":{"rendered":"Python \u3067\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u306e\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">2 \u3064\u306e\u30d9\u30af\u30c8\u30eb<em>A<\/em>\u3068<em>B<\/em>\u306e\u9593\u306e<strong>\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2<\/strong>\u306f\u6b21\u306e\u3088\u3046\u306b\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u03a3|A <sub>i<\/sub> \u2013 B <sub>i<\/sub> |<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u3053\u3067\u3001 <em>i<\/em>\u306f\u5404\u30d9\u30af\u30c8\u30eb\u306e i<sup>\u756a\u76ee\u306e<\/sup>\u8981\u7d20\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u8ddd\u96e2\u306f 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u975e\u985e\u4f3c\u6027\u3092\u6e2c\u5b9a\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u3001\u591a\u304f\u306e<a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/a>\u3067\u4e00\u822c\u7684\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b 2 \u3064\u306e\u65b9\u6cd5\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 1: \u30ab\u30b9\u30bf\u30e0\u95a2\u6570\u3092\u4f5c\u6210\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001Python \u3067 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u30ab\u30b9\u30bf\u30e0\u95a2\u6570\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">from<\/span> math <span style=\"color: #008000;\">import<\/span> sqrt\n\n<span style=\"color: #008080;\">#create function to calculate Manhattan distance<\/span> \n<span style=\"color: #008000;\">def<\/span> manhattan(a, b):\n    <span style=\"color: #008000;\">return<\/span> <span style=\"color: #3366ff;\">sum<\/span> ( <span style=\"color: #3366ff;\">abs<\/span> (val1-val2) <span style=\"color: #008000;\">for<\/span> val1, val2 <span style=\"color: #008000;\">in<\/span> <span style=\"color: #3366ff;\">zip<\/span> (a,b))\n \n<span style=\"color: #008080;\">#definevectors\n<\/span>A = [2, 4, 4, 6]\nB = [5, 5, 7, 8]\n\n<span style=\"color: #008080;\">#calculate Manhattan distance between vectors\n<\/span>manhattan(A,B)\n\n9<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u306f<strong>9<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u307e\u3067\u306e\u8ddd\u96e2\u3092\u624b\u52d5\u3067\u3059\u3070\u3084\u304f\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u3001\u3053\u308c\u304c\u6b63\u3057\u3044\u3053\u3068\u3092\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u03a3|A <sub>i<\/sub> \u2013 B <sub>i<\/sub> | = |2-5| + |4-5| + |4-7| + |6-8| = 3 + 1 + 3 + 2 = <strong>9<\/strong> \u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 2: cityblock() \u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u5225\u306e\u65b9\u6cd5\u306f\u3001SciPy \u30d1\u30c3\u30b1\u30fc\u30b8\u306e<a href=\"https:\/\/docs.scipy.org\/doc\/scipy\/reference\/generated\/scipy.spatial.distance.cityblock.html\" target=\"_blank\" rel=\"noopener\">cityblock()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">spatial<\/span> . <span style=\"color: #3366ff;\">distance<\/span> <span style=\"color: #008000;\">import<\/span> cityblock\n\n<span style=\"color: #008080;\">#definevectors\n<\/span>A = [2, 4, 4, 6]\nB = [5, 5, 7, 8]\n\n<span style=\"color: #008080;\">#calculate Manhattan distance between vectors\n<\/span>cityblock(A, B)\n\n9<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3082\u3046\u4e00\u5ea6\u8a00\u3044\u307e\u3059\u304c\u3001\u3053\u308c\u3089 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u306f<strong>9<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e 2 \u3064\u306e\u5217\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u3082\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">spatial<\/span> . <span style=\"color: #3366ff;\">distance<\/span> <span style=\"color: #008000;\">import<\/span> cityblock\n<span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">A<\/span> ': [2, 4, 4, 6],\n                   ' <span style=\"color: #ff0000;\">B<\/span> ': [5, 5, 7, 8],\n                   ' <span style=\"color: #ff0000;\">C<\/span> ': [9, 12, 12, 13]})\n\n<span style=\"color: #008080;\">#calculate Manhattan distance between columns A and B<\/span>\ncityblock(df. <span style=\"color: #3366ff;\">A<\/span> , df. <span style=\"color: #3366ff;\">B<\/span> )\n\n9<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/\u30e6\u30fc\u30af\u30ea\u30c3\u30c8\u3099\u8ddd\u96e2python\/\" target=\"_blank\" rel=\"noopener\">Python\u3067\u30e6\u30fc\u30af\u30ea\u30c3\u30c9\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/python\u306e\u30cf\u30df\u30f3\u30af\u3099\u8ddd\u96e2\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u30cf\u30df\u30f3\u30b0\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/python\u306e\u30ec\u30fc\u30d8\u3099\u30f3\u30b7\u30e5\u30bf\u30a4\u30f3\u8ddd\u96e2\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u30ec\u30fc\u30d9\u30f3\u30b7\u30e5\u30bf\u30a4\u30f3\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30de\u30cf\u30e9\u30ce\u30d2\u3099\u30b9\u30ea\u30e2\u30fc\u30c8python\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u30de\u30cf\u30e9\u30ce\u30d3\u30b9\u8ddd\u96e2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>2 \u3064\u306e\u30d9\u30af\u30c8\u30ebA\u3068B\u306e\u9593\u306e\u30de\u30f3\u30cf\u30c3\u30bf\u30f3\u8ddd\u96e2\u306f\u6b21\u306e\u3088\u3046\u306b\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002 \u03a3|A i \u2013 B i | \u3053\u3053\u3067\u3001 i\u306f\u5404\u30d9\u30af\u30c8\u30eb\u306e i\u756a\u76ee\u306e\u8981\u7d20\u3067\u3059\u3002 \u3053\u306e\u8ddd\u96e2\u306f 2 \u3064\u306e\u30d9\u30af\u30c8\u30eb\u9593\u306e\u975e\u985e\u4f3c\u6027\u3092\u6e2c\u5b9a\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u3001\u591a\u304f\u306e [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1654","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python 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