{"id":1782,"date":"2023-07-25T00:23:37","date_gmt":"2023-07-25T00:23:37","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%80%e1%85%a1-%e1%84%86%e1%85%a9%e1%84%83%e1%85%a6%e1%86%af%e1%84%8b%e1%85%b5-%e1%84%83%e1%85%ac%e1%84%83%e1%85%a1\/"},"modified":"2023-07-25T00:23:37","modified_gmt":"2023-07-25T00:23:37","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%80%e1%85%a1-%e1%84%86%e1%85%a9%e1%84%83%e1%85%a6%e1%86%af%e1%84%8b%e1%85%b5-%e1%84%83%e1%85%ac%e1%84%83%e1%85%a1","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%80%e1%85%a1-%e1%84%86%e1%85%a9%e1%84%83%e1%85%a6%e1%86%af%e1%84%8b%e1%85%b5-%e1%84%83%e1%85%ac%e1%84%83%e1%85%a1\/","title":{"rendered":"Pandas get dummies\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95 \u2013 pd.get_dummies"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\uc885\uc885 \ud1b5\uacc4\uc5d0\uc11c \uc6b0\ub9ac\uac00 \uc791\uc5c5\ud558\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0\ub294 <a href=\"https:\/\/statorials.org\/ko\/\u1107\u1165\u11b7\u110c\u116e\u1112\u1167\u11bc-\u1103\u1162-\u110b\u1163\u11bc\u110c\u1165\u11a8\/\" target=\"_blank\" rel=\"noopener\">\ubc94\uc8fc\ud615 \ubcc0\uc218\uac00<\/a> \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub984\uc774\ub098 \ub77c\ubca8\uc744 \ucde8\ud558\ub294 \ubcc0\uc218\uc785\ub2c8\ub2e4. \uc608\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uacb0\ud63c \uc0c1\ud0dc(\u201c\uae30\ud63c\u201d, \u201c\ubbf8\ud63c\u201d, \u201c\uc774\ud63c\u201d)<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud761\uc5f0 \uc0c1\ud0dc(&#8216;\ud761\uc5f0\uc790&#8217;, &#8216;\ube44\ud761\uc5f0\uc790&#8217;)<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ub208 \uc0c9\uae54(\u201c\ud30c\ub780\uc0c9\u201d, \u201c\ub179\uc0c9\u201d, \u201c\uac1c\uc554\uc0c9\u201d)<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uad50\uc721 \uc218\uc900(\uc608: &#8216;\uace0\ub4f1\ud559\uad50&#8217;, &#8216;\ud559\uc0ac \ud559\uc704&#8217;, &#8216;\uc11d\uc0ac \ud559\uc704&#8217;)<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uae30\uacc4 \ud559\uc2b5 \uc54c\uace0\ub9ac\uc998(\uc608: <a href=\"https:\/\/statorials.org\/ko\/\u1103\u1161\u110c\u116e\u11bc-\u1109\u1165\u11ab\u1112\u1167\u11bc-\u1112\u116c\u1100\u1171\/\" target=\"_blank\" rel=\"noopener\">\uc120\ud615 \ud68c\uadc0<\/a> , <a href=\"https:\/\/statorials.org\/ko\/\u1105\u1169\u110c\u1175\u1109\u1173\u1110\u1175\u11a8-\u1112\u116c\u1100\u1171-1\/\" target=\"_blank\" rel=\"noopener\">\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0<\/a> , <a href=\"https:\/\/statorials.org\/ko\/\u1106\u116e\u110c\u1161\u11a8\u110b\u1171-\u1112\u116e\u11ab\u1105\u1167\u11ab\/\" target=\"_blank\" rel=\"noopener\">\ub79c\ub364 \ud3ec\ub808\uc2a4\ud2b8<\/a> \ub4f1)\uc744 \uc870\uc815\ud560 \ub54c \ubc94\uc8fc\ud615 \ubcc0\uc218\ub97c \ubc94\uc8fc\ud615 \ub370\uc774\ud130\ub97c \ub098\ud0c0\ub0b4\ub294 \ub370 \uc0ac\uc6a9\ub418\ub294 \uc218\uce58 \ubcc0\uc218\uc778 \ub354\ubbf8 <strong>\ubcc0\uc218<\/strong> \ub85c \ubcc0\ud658\ud558\ub294 \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4 \ubc94\uc8fc\ud615 \ubcc0\uc218 <strong>Gender \uac00<\/strong> \ud3ec\ud568\ub41c \ub370\uc774\ud130\uc138\ud2b8\uac00 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4. \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \uc774 \ubcc0\uc218\ub97c \uc608\uce21 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\ub824\uba74 \uba3c\uc800 \uc774\ub97c \ub354\ubbf8 \ubcc0\uc218\ub85c \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ub354\ubbf8 \ubcc0\uc218\ub97c \uc0dd\uc131\ud558\ub824\uba74 0\uc744 \ub098\ud0c0\ub0b4\ub294 \uac12(&#8220;\ub0a8\uc131&#8221;) \uc911 \ud558\ub098\ub97c \uc120\ud0dd\ud558\uace0 1\uc744 \ub098\ud0c0\ub0b4\ub294 \ub2e4\ub978 \uac12(&#8220;\uc5ec\uc131&#8221;)\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/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\uc5d0\uc11c \ub354\ubbf8 \ubcc0\uc218\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">pandas DataFrame\uc758 \ubcc0\uc218\uc5d0 \ub300\ud55c \ub354\ubbf8\ub97c \uc0dd\uc131\ud558\ub824\uba74 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.get_dummies.html\" target=\"_blank\" rel=\"noopener\">pandas.get_dummies()<\/a> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">pandas.get_dummies(\ub370\uc774\ud130, \uc811\ub450\uc0ac=\uc5c6\uc74c, \uc5f4=\uc5c6\uc74c, drop_first=False)<\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>data<\/strong> : \ud32c\ub354 DataFrame\uc758 \uc774\ub984<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>prefix<\/strong> : \uc0c8\ub85c\uc6b4 \ub354\ubbf8 \ubcc0\uc218 \uc5f4\uc758 \uc2dc\uc791 \ubd80\ubd84\uc5d0 \ucd94\uac00\ud560 \ubb38\uc790\uc5f4<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>columns<\/strong> : \ub354\ubbf8\ubcc0\uc218\ub85c \ubcc0\ud658\ud560 \uc5f4\uc758 \uc774\ub984<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>drop_first<\/strong> : \uccab \ubc88\uc9f8 \ub354\ubbf8\ubcc0\uc218 \uc5f4 \uc0ad\uc81c \uc5ec\ubd80<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 1: \ub2e8\uc77c \ub354\ubbf8 \ubcc0\uc218 \uc0dd\uc131<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/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> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc131\ubcc4\uc744 \ub354\ubbf8 \ubcc0\uc218\ub85c \ubc14\uafc0 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/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;\">\uc131\ubcc4 \uc5f4\uc740 \uc774\uc81c \ub2e4\uc74c\uacfc \uac19\uc740 \ub354\ubbf8 \ubcc0\uc218\uc785\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> \uac12\uc740 &#8220;\uc5ec\uc131&#8221;\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uac12 <strong>1<\/strong> \uc740 &#8216;\ub0a8\uc131&#8217;\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: \uc5ec\ub7ec \ub354\ubbf8 \ubcc0\uc218 \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/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> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc131\ubcc4\uacfc \ub300\ud559\uc744 \ub354\ubbf8 \ubcc0\uc218\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/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;\">\uc131\ubcc4 \uc5f4\uc740 \uc774\uc81c \ub2e4\uc74c\uacfc \uac19\uc740 \ub354\ubbf8 \ubcc0\uc218\uc785\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> \uac12\uc740 &#8220;\uc5ec\uc131&#8221;\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uac12 <strong>1<\/strong> \uc740 &#8216;\ub0a8\uc131&#8217;\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uadf8\ub9ac\uace0 \ub300\ud559 \uc5f4\uc740 \uc774\uc81c \ub2e4\uc74c\uacfc \uac19\uc740 \ub354\ubbf8 \ubcc0\uc218\uc785\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> \uac12\uc740 &#8220;\uc544\ub2c8\uc694&#8221; \ub300\ud559\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uac12 <strong>1<\/strong> \uc740 \ub300\ud559\uc5d0 \ub300\ud55c &#8220;\uc608&#8221;\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1112\u116c\u1100\u1171-\u1103\u1165\u1106\u1175-\u1107\u1167\u11ab\u1109\u116e\/\" target=\"_blank\" rel=\"noopener\">\ud68c\uadc0\ubd84\uc11d\uc5d0\uc11c \ub354\ubbf8\ubcc0\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1103\u1165\u1106\u1175-\u1107\u1167\u11ab\u1109\u116e-\u1110\u1173\u1105\u1162\u11b8\/\" target=\"_blank\" rel=\"noopener\">\ub354\ubbf8 \ubcc0\uc218 \ud2b8\ub7a9\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc885\uc885 \ud1b5\uacc4\uc5d0\uc11c \uc6b0\ub9ac\uac00 \uc791\uc5c5\ud558\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0\ub294 \ubc94\uc8fc\ud615 \ubcc0\uc218\uac00 \ud3ec\ud568\ub429\ub2c8\ub2e4. \uc774\ub984\uc774\ub098 \ub77c\ubca8\uc744 \ucde8\ud558\ub294 \ubcc0\uc218\uc785\ub2c8\ub2e4. \uc608\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4: \uacb0\ud63c \uc0c1\ud0dc(\u201c\uae30\ud63c\u201d, \u201c\ubbf8\ud63c\u201d, \u201c\uc774\ud63c\u201d) \ud761\uc5f0 \uc0c1\ud0dc(&#8216;\ud761\uc5f0\uc790&#8217;, &#8216;\ube44\ud761\uc5f0\uc790&#8217;) \ub208 \uc0c9\uae54(\u201c\ud30c\ub780\uc0c9\u201d, \u201c\ub179\uc0c9\u201d, \u201c\uac1c\uc554\uc0c9\u201d) \uad50\uc721 \uc218\uc900(\uc608: &#8216;\uace0\ub4f1\ud559\uad50&#8217;, &#8216;\ud559\uc0ac \ud559\uc704&#8217;, &#8216;\uc11d\uc0ac \ud559\uc704&#8217;) \uae30\uacc4 \ud559\uc2b5 \uc54c\uace0\ub9ac\uc998(\uc608: \uc120\ud615 \ud68c\uadc0 , \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 , \ub79c\ub364 \ud3ec\ub808\uc2a4\ud2b8 \ub4f1)\uc744 \uc870\uc815\ud560 \ub54c \ubc94\uc8fc\ud615 \ubcc0\uc218\ub97c \ubc94\uc8fc\ud615 \ub370\uc774\ud130\ub97c \ub098\ud0c0\ub0b4\ub294 \ub370 \uc0ac\uc6a9\ub418\ub294 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1782","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas Get Dummies\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95 - pd.get_dummies<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c pandas.get_dummies() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec 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