{"id":1781,"date":"2023-07-25T00:23:37","date_gmt":"2023-07-25T00:23:37","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%8b%e3%82%99%e3%83%a2%e3%83%86%e3%82%99%e3%83%ab%e3%81%ab%e3%81%aa%e3%82%8b\/"},"modified":"2023-07-25T00:23:37","modified_gmt":"2023-07-25T00:23:37","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%8b%e3%82%99%e3%83%a2%e3%83%86%e3%82%99%e3%83%ab%e3%81%ab%e3%81%aa%e3%82%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%8b%e3%82%99%e3%83%a2%e3%83%86%e3%82%99%e3%83%ab%e3%81%ab%e3%81%aa%e3%82%8b\/","title":{"rendered":"Pandas get dummies \u306e\u4f7f\u7528\u65b9\u6cd5 \u2013 pd.get_dummies"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u7d71\u8a08\u3067\u306f\u3001\u6271\u3046\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b<a href=\"https:\/\/statorials.org\/ja\/\u30ab\u30c6\u30b3\u3099\u30ea\u7684-vs-\u5b9a\u91cf\u7684\/\" target=\"_blank\" rel=\"noopener\">\u30ab\u30c6\u30b4\u30ea\u5909\u6570\u304c<\/a>\u542b\u307e\u308c\u308b\u3053\u3068\u304c\u3088\u304f\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089\u306f\u3001\u540d\u524d\u307e\u305f\u306f\u30e9\u30d9\u30eb\u3092\u53d6\u308b\u5909\u6570\u3067\u3059\u3002\u4f8b\u3068\u3057\u3066\u306f\u6b21\u306e\u3082\u306e\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5a5a\u59fb\u72b6\u6cc1\uff08\u300c\u65e2\u5a5a\u300d\u3001\u300c\u72ec\u8eab\u300d\u3001\u300c\u96e2\u5a5a\u300d\uff09<\/span><\/li>\n<li><span style=\"color: #000000;\">\u55ab\u7159\u72b6\u6cc1\uff08\u300c\u55ab\u7159\u8005\u300d\u3001\u300c\u975e\u55ab\u7159\u8005\u300d\uff09<\/span><\/li>\n<li><span style=\"color: #000000;\">\u76ee\u306e\u8272\uff08\u300c\u30d6\u30eb\u30fc\u300d\u3001\u300c\u30b0\u30ea\u30fc\u30f3\u300d\u3001\u300c\u30d8\u30fc\u30bc\u30eb\u300d\uff09<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5b66\u6b74\uff08\u4f8b\uff1a\u300c\u9ad8\u6821\u300d\u3001\u300c\u5b66\u58eb\u300d\u3001\u300c\u4fee\u58eb\u300d\uff09<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0 (<a href=\"https:\/\/statorials.org\/ja\/\u91cd\u7dda\u5f62\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener\">\u7dda\u5f62\u56de\u5e30<\/a>\u3001 <a href=\"https:\/\/statorials.org\/ja\/\u30ed\u30b7\u3099\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30-1\/\" target=\"_blank\" rel=\"noopener\">\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30<\/a>\u3001<a href=\"https:\/\/statorials.org\/ja\/\u30e9\u30f3\u30bf\u3099\u30e0\u30c8\u3099\u30ea\u30eb\/\" target=\"_blank\" rel=\"noopener\">\u30e9\u30f3\u30c0\u30e0 \u30d5\u30a9\u30ec\u30b9\u30c8<\/a>\u306a\u3069) \u3092\u8abf\u6574\u3059\u308b\u5834\u5408\u3001\u591a\u304f\u306e\u5834\u5408\u3001\u30ab\u30c6\u30b4\u30ea\u5909\u6570\u3092\u3001\u30ab\u30c6\u30b4\u30ea\u30c7\u30fc\u30bf\u3092\u8868\u3059\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u308b\u6570\u5024\u5909\u6570\u3067\u3042\u308b<strong>\u30c0\u30df\u30fc\u5909\u6570<\/strong>\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3068\u3048\u3070\u3001\u30ab\u30c6\u30b4\u30ea\u5909\u6570<strong>Gender<\/strong>\u3092\u542b\u3080\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002\u3053\u306e\u5909\u6570\u3092\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u4e88\u6e2c\u5b50\u3068\u3057\u3066\u4f7f\u7528\u3059\u308b\u306b\u306f\u3001\u307e\u305a\u305d\u308c\u3092\u30c0\u30df\u30fc\u5909\u6570\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c0\u30df\u30fc\u5909\u6570\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u30010 \u3092\u8868\u3059\u5024\u306e 1 \u3064 (\u300c\u7537\u6027\u300d) \u3092\u9078\u629e\u3057\u30011 \u3092\u8868\u3059\u3082\u3046 1 \u3064\u306e\u5024 (\u300c\u5973\u6027\u300d) \u3092\u9078\u629e\u3057\u307e\u3059\u3002<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-13941 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mannequin2.png\" alt=\"\" width=\"540\" height=\"312\" srcset=\"\" sizes=\"auto, \"><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Pandas\u3067\u30c0\u30df\u30fc\u5909\u6570\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">pandas DataFrame \u5185\u306e\u5909\u6570\u306e\u30c0\u30df\u30fc\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3059\u308b<a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.get_dummies.html\" target=\"_blank\" rel=\"noopener\">pandas.get_dummies()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">pandas.get_dummies(\u30c7\u30fc\u30bf\u3001\u30d7\u30ec\u30d5\u30a3\u30c3\u30af\u30b9=\u306a\u3057\u3001\u5217=\u306a\u3057\u3001drop_first=False)<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>data<\/strong> : \u30d1\u30f3\u30c0\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u540d\u524d<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>prefix<\/strong> : \u65b0\u3057\u3044\u30c0\u30df\u30fc\u5909\u6570\u5217\u306e\u5148\u982d\u306b\u8ffd\u52a0\u3059\u308b\u6587\u5b57\u5217<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>columns<\/strong> : \u30c0\u30df\u30fc\u5909\u6570\u306b\u5909\u63db\u3059\u308b\u5217\u306e\u540d\u524d<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>drop_first<\/strong> : \u6700\u521d\u306e\u30c0\u30df\u30fc\u5909\u6570\u5217\u3092\u524a\u9664\u3059\u308b\u304b\u3069\u3046\u304b<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 1: \u5358\u4e00\u306e\u30c0\u30df\u30fc\u5909\u6570\u3092\u4f5c\u6210\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">income<\/span> ': [45, 48, 54, 57, 65, 69, 78],\n                   ' <span style=\"color: #ff0000;\">age<\/span> ': [23, 25, 24, 29, 38, 36, 40],\n                   ' <span style=\"color: #ff0000;\">gender<\/span> ': ['M', 'F', 'M', 'F', 'F', 'F', 'M']})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        income age gender\n0 45 23 M\n1 48 25 F\n2 54 24 M\n3 57 29 F\n4 65 38 F\n5 69 36 F\n6 78 40 M<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>pd.get_dummies()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u6027\u5225\u3092\u30c0\u30df\u30fc\u5909\u6570\u306b\u5909\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert gender to dummy variable<\/span>\np.d. <span style=\"color: #3366ff;\">get_dummies<\/span> (df, columns=[' <span style=\"color: #ff0000;\">gender<\/span> '], drop_first= <span style=\"color: #008000;\">True<\/span> )\n\n\tincome age gender_M\n0 45 23 1\n1 48 25 0\n2 54 24 1\n3 57 29 0\n4 65 38 0\n5 69 36 0\n6 78 40 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6027\u5225\u5217\u306f\u30c0\u30df\u30fc\u5909\u6570\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5024<strong>0<\/strong>\u306f\u300c\u5973\u6027\u300d\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5024<strong>1<\/strong>\u306f\u300c\u7537\u6027\u300d\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 2: \u8907\u6570\u306e\u30c0\u30df\u30fc\u5909\u6570\u3092\u4f5c\u6210\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">income<\/span> ': [45, 48, 54, 57, 65, 69, 78],\n                   ' <span style=\"color: #ff0000;\">age<\/span> ': [23, 25, 24, 29, 38, 36, 40],\n                   ' <span style=\"color: #ff0000;\">gender<\/span> ': ['M', 'F', 'M', 'F', 'F', 'F', 'M'],\n                   ' <span style=\"color: #ff0000;\">college<\/span> ': ['Y', 'N', 'N', 'N', 'Y', 'Y', 'Y']})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tincome age gender college\n0 45 23 M Y\n1 48 25 F N\n2 54 24 M N\n3 57 29 F N\n4 65 38 F Y\n5 69 36 F Y\n6 78 40 M Y<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>pd.get_dummies()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u6027\u5225\u3068\u5927\u5b66\u3092\u30c0\u30df\u30fc\u5909\u6570\u306b\u5909\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert gender to dummy variable<\/span>\np.d. <span style=\"color: #3366ff;\">get_dummies<\/span> (df, columns=[' <span style=\"color: #ff0000;\">gender<\/span> ', ' <span style=\"color: #ff0000;\">college<\/span> '], drop_first= <span style=\"color: #008000;\">True<\/span> )\n\n\n        income age gender_M college_Y\n0 45 23 1 1\n1 48 25 0 0\n2 54 24 1 0\n3 57 29 0 0\n4 65 38 0 1\n5 69 36 0 1\n6 78 40 1 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6027\u5225\u5217\u306f\u30c0\u30df\u30fc\u5909\u6570\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5024<strong>0<\/strong>\u306f\u300c\u5973\u6027\u300d\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5024<strong>1<\/strong>\u306f\u300c\u7537\u6027\u300d\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u305d\u3057\u3066\u3001college \u5217\u306f\u30c0\u30df\u30fc\u5909\u6570\u306b\u306a\u308a\u307e\u3057\u305f\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5024<strong>0<\/strong>\u306f\u300c\u3044\u3044\u3048\u300d\u306e\u5927\u5b66\u3092\u8868\u3057\u307e\u3059<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5024<strong>1<\/strong>\u306f\u5927\u5b66\u3078\u306e\u300c\u306f\u3044\u300d\u3092\u8868\u3057\u307e\u3059<\/span><\/li>\n<\/ul>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/\u56de\u5e30\u30bf\u3099\u30df\u30fc\u5909\u6570\/\" target=\"_blank\" rel=\"noopener\">\u56de\u5e30\u5206\u6790\u3067\u30c0\u30df\u30fc\u5909\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30bf\u3099\u30df\u30fc\u5909\u6570\u30c8\u30e9\u30c3\u30d5\u309a\/\" target=\"_blank\" rel=\"noopener\">\u30c0\u30df\u30fc\u5909\u6570\u30c8\u30e9\u30c3\u30d7\u3068\u306f\u4f55\u3067\u3059\u304b?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7d71\u8a08\u3067\u306f\u3001\u6271\u3046\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u30ab\u30c6\u30b4\u30ea\u5909\u6570\u304c\u542b\u307e\u308c\u308b\u3053\u3068\u304c\u3088\u304f\u3042\u308a\u307e\u3059\u3002 \u3053\u308c\u3089\u306f\u3001\u540d\u524d\u307e\u305f\u306f\u30e9\u30d9\u30eb\u3092\u53d6\u308b\u5909\u6570\u3067\u3059\u3002\u4f8b\u3068\u3057\u3066\u306f\u6b21\u306e\u3082\u306e\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002 \u5a5a\u59fb\u72b6\u6cc1\uff08\u300c\u65e2\u5a5a\u300d\u3001\u300c\u72ec\u8eab\u300d\u3001\u300c\u96e2\u5a5a\u300d\uff09 \u55ab\u7159\u72b6\u6cc1\uff08\u300c\u55ab\u7159\u8005\u300d\u3001\u300c\u975e\u55ab [&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-1781","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>Pandas Get Dummies \u306e\u4f7f\u7528\u65b9\u6cd5 - pd.get_dummies<\/title>\n<meta name=\"description\" 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