{"id":2514,"date":"2023-07-21T22:38:17","date_gmt":"2023-07-21T22:38:17","guid":{"rendered":"https:\/\/statorials.org\/ja\/python%e3%81%a6%e3%82%99%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf%e3%81%ae%e3%82%af%e3%82%99%e3%83%ab%e3%83%bc%e3%83%95%e3%82%9a%e5%8c%96\/"},"modified":"2023-07-21T22:38:17","modified_gmt":"2023-07-21T22:38:17","slug":"python%e3%81%a6%e3%82%99%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf%e3%81%ae%e3%82%af%e3%82%99%e3%83%ab%e3%83%bc%e3%83%95%e3%82%9a%e5%8c%96","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python%e3%81%a6%e3%82%99%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf%e3%81%ae%e3%82%af%e3%82%99%e3%83%ab%e3%83%bc%e3%83%95%e3%82%9a%e5%8c%96\/","title":{"rendered":"Python \u3067\u30c7\u30fc\u30bf\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3059\u308b\u65b9\u6cd5: \u4f8b\u4ed8\u304d"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u3067\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\n\n#perform binning with 3 bins<\/span>\ndf[' new_bin<\/span> '] = pd. qcut<\/span> (df[' variable_name<\/span> '], q= 3<\/span> )\n<\/strong><\/pre>\n
\u6b21\u306e\u4f8b\u306f\u3001\u5b9f\u969b\u306b\u6b21\u306e pandas DataFrame \u3067\u3053\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' points<\/span> ': [4, 4, 7, 8, 12, 13, 15, 18, 22, 23, 23, 25],\n                   ' assists<\/span> ': [2, 5, 4, 7, 7, 8, 5, 4, 5, 11, 13, 8],\n                   ' rebounds<\/span> ': [7, 7, 4, 6, 3, 8, 9, 9, 12, 11, 8, 9]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds\n0 4 2 7\n1 4 5 7\n2 7 4 4\n3 8 7 6\n4 12 7 3\n5 13 8 8\n6 15 5 9\n7 18 4 9\n8 22 5 12\n9 23 11 11\n10 23 13 8\n11 25 8 9\n<\/span><\/span><\/strong><\/pre>\n
\u4f8b1: \u30de\u30b9\u30bf\u30fc\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u7279\u5b9a\u306e\u30d6\u30ec\u30fc\u30af \u30de\u30fc\u30af\u3092\u542b\u3080qcut()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001 points<\/strong>\u5909\u6570\u3067\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 #perform data binning on variable points<\/em>\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '], q= 3<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 (3,999, 10,667]\n1 4 5 7 (3,999, 10,667]\n2 7 4 4 (3,999, 10,667]\n3 8 7 6 (3,999, 10,667]\n4 12 7 3 (10,667, 19,333]\n5 13 8 8 (10,667, 19,333]\n6 15 5 9 (10,667, 19,333]\n7 18 4 9 (10,667, 19,333]\n8 22 5 12 (19.333, 25.0]\n9 23 11 11 (19.333, 25.0]\n10 23 13 8 (19.333, 25.0]\n11 25 8 9 (19.333, 25.0]\n<\/span><\/span><\/strong><\/pre>\n
\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u5404\u884c\u306f\u3001\u30dd\u30a4\u30f3\u30c8\u5217\u306e\u5024\u306b\u57fa\u3065\u3044\u3066 3 \u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u3044\u305a\u308c\u304b\u306b\u914d\u7f6e\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
 value_counts()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u5404\u30d3\u30f3\u306b\u914d\u7f6e\u3055\u308c\u305f\u884c\u6570\u3092\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #count frequency of each bin\n<\/span>df[' points_bin<\/span> ']. value_counts<\/span> ()\n\n(3,999, 10,667] 4\n(10.667, 19.333] 4\n(19.333, 25.0] 4\nName: points_bin, dtype: int64\n<\/span><\/span><\/strong><\/pre>\n
\u5404\u30d3\u30f3\u306b 4 \u3064\u306e\u89b3\u6e2c\u5024\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b 2: \u7279\u5b9a\u306e\u5206\u4f4d\u5024\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf \u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b<\/strong><\/span><\/h3>\n
\u7279\u5b9a\u306e\u5206\u4f4d\u6570\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf \u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #perform data binning on variable points<\/em> with specific quantiles\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '], q=[0, .2, .4, .6, .8, 1])\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 (3.999, 7.2]\n1 4 5 7 (3.999, 7.2]\n2 7 4 4 (3.999, 7.2]\n3 8 7 6 (7.2, 12.4]\n4 12 7 3 (7.2, 12.4]\n5 13 8 8 (12.4, 16.8]\n6 15 5 9 (12.4, 16.8]\n7 18 4 9 (16.8, 22.8]\n8 22 5 12 (16.8, 22.8]\n9 23 11 11 (22.8, 25.0]\n10 23 13 8 (22.8, 25.0]\n11 25 8 9 (22.8, 25.0]\n<\/span><\/span><\/strong><\/pre>\n
\u4f8b 3:<\/strong><\/span>\u30e9\u30d9\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3059\u308b<\/strong><\/span><\/h3>\n
\u7279\u5b9a\u306e\u5206\u4f4d\u6570\u3068\u30e9\u30d9\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #perform data binning on points<\/em> variable with specific quantiles and labels\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '],\n                           q=[0, .2, .4, .6, .8, 1],\n                           labels=[' A<\/span> ',' B<\/span> ',' C<\/span> ',' D<\/span> ',' E<\/span> '])\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 A\n1 4 5 7 A\n2 7 4 4 A\n3 8 7 6 B\n4 12 7 3 B\n5 13 8 8 C\n6 15 5 9 C\n7 18 4 9 D\n8 22 5 12 D\n9 23 11 11 E\n10 23 13 8 E\n11 25 8 9 E\n<\/span><\/span><\/strong><\/pre>\n
\u5404\u884c\u306b\u306f\u30dd\u30a4\u30f3\u30c8<\/strong>\u5217\u306e\u5024\u306b\u57fa\u3065\u3044\u3066\u30d3\u30f3\u304c\u5272\u308a\u5f53\u3066\u3089\u308c\u3066\u304a\u308a\u3001\u30d3\u30f3\u306b\u306f\u6587\u5b57\u3092\u4f7f\u7528\u3057\u3066\u30e9\u30d9\u30eb\u304c\u4ed8\u3051\u3089\u308c\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u30d1\u30f3\u30c0: value_counts() \u95a2\u6570\u306e\u4f7f\u7528\u65b9\u6cd5<\/a>
Pandas: \u5024\u306e\u6570\u3092\u542b\u3080\u30d4\u30dc\u30c3\u30c8 \u30c6\u30fc\u30d6\u30eb\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a>
\u30d1\u30f3\u30c0: \u5217\u5185\u306e\u7279\u5b9a\u306e\u5024\u306e\u51fa\u73fe\u3092\u6570\u3048\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u3067\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002 import pandas as pd #perform binning with 3 bins df[‘ new_bin  […]<\/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-2514","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPython \u3067\u30c7\u30fc\u30bf \u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5 (\u4f8b\u3042\u308a) - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u30c7\u30fc\u30bf\u306e\u30b0\u30eb\u30fc\u30d7\u5316\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/python\u3066\u3099\u306e\u30c6\u3099\u30fc\u30bf\u306e\u30af\u3099\u30eb\u30fc\u30d5\u309a\u5316\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python \u3067\u30c7\u30fc\u30bf \u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5 (\u4f8b\u3042\u308a) - 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