{"id":2077,"date":"2023-07-23T19:27:32","date_gmt":"2023-07-23T19:27:32","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2\/"},"modified":"2023-07-23T19:27:32","modified_gmt":"2023-07-23T19:27:32","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2\/","title":{"rendered":"Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\uc885\uc885 \ud1b5\uacc4 \ubc0f \uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c\ub294 \uac12\uc758 \ubc94\uc704\uac00 0\uacfc 1 \uc0ac\uc774\uac00 \ub418\ub3c4\ub85d \ubcc0\uc218\ub97c <strong>\uc815\uaddc\ud654\ud569\ub2c8\ub2e4<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud558\ub294 \uac00\uc7a5 \uc77c\ubc18\uc801\uc778 \uc774\uc720\ub294 \uc77c\uc885\uc758 \ub2e4\ubcc0\ub7c9 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uace0(\uc608: \uc5ec\ub7ec \uc608\uce21 \ubcc0\uc218\uc640 \ubc18\uc751 \ubcc0\uc218 \uac04\uc758 \uad00\uacc4\ub97c \uc774\ud574\ud558\uace0 \uc2f6\uace0) \uac01 \ubcc0\uc218\uac00 \ubd84\uc11d\uc5d0 \ub3d9\uc77c\ud558\uac8c \uae30\uc5ec\ud558\uae30\ub97c \uc6d0\ud560 \ub54c\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ubcc0\uc218\ub97c \ub2e4\uc591\ud55c \uaddc\ubaa8\ub85c \uce21\uc815\ud558\uba74 \ubd84\uc11d\uc5d0 \ub3d9\uc77c\ud558\uac8c \uae30\uc5ec\ud558\uc9c0 \uc54a\ub294 \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \ud55c \ubcc0\uc218\uc758 \uac12\uc774 0~100,000\uc774\uace0 \ub2e4\ub978 \ubcc0\uc218\uc758 \uac12\uc774 0~100\uc778 \uacbd\uc6b0 \ubd84\uc11d\uc5d0\uc11c\ub294 \ubc94\uc704\uac00 \ud070 \ubcc0\uc218\uc5d0 \ub354 \ud070 \uac00\uc911\uce58\uac00 \ud560\ub2f9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ubcc0\uc218\ub97c \ud45c\uc900\ud654\ud568\uc73c\ub85c\uc368 \uac01 \ubcc0\uc218\uac00 \ubd84\uc11d\uc5d0 \ub3d9\uc77c\ud558\uac8c \uae30\uc5ec\ud558\ub294\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">0\uacfc 1 \uc0ac\uc774\uc758 \uac12\uc744 \uc815\uaddc\ud654\ud558\ub824\uba74 \ub2e4\uc74c \uacf5\uc2dd\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>x <sub>\ub178\ub984<\/sub> = (x <sub>i<\/sub> \u2013 x <sub>\ucd5c\uc18c<\/sub> ) \/ (x <sub>\ucd5c\ub300<\/sub> \u2013 x <sub>\ucd5c\uc18c<\/sub> )<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x <sub>norm<\/sub> :<\/strong> \ub370\uc774\ud130\uc138\ud2b8\uc758 <sup>i\ubc88\uc9f8<\/sup> \uc815\uaddc\ud654\ub41c \uac12<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>x <sub>i<\/sub> :<\/strong> \ub370\uc774\ud130\uc138\ud2b8\uc758 <sup>i\ubc88\uc9f8<\/sup> \uac12<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>x <sub>max<\/sub><\/strong> : \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ucd5c\uc18c\uac12<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>x <sub>min<\/sub> :<\/strong> \ub370\uc774\ud130\uc138\ud2b8\uc758 \ucd5c\ub300\uac12<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc81c\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ud558\ub098 \uc774\uc0c1\uc758 \ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 1: NumPy \ubc30\uc5f4 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 NumPy \ubc30\uc5f4\uc758 \ubaa8\ub4e0 \uac12\uc744 \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np \n\n<span style=\"color: #008080;\">#create NumPy array\n<\/span>data = np. <span style=\"color: #3366ff;\">array<\/span> ([[13, 16, 19, 22, 23, 38, 47, 56, 58, 63, 65, 70, 71]])\n\n<span style=\"color: #008080;\">#normalize all values in array\n<\/span>data_norm = (data - data. <span style=\"color: #3366ff;\">min<\/span> ())\/ (data. <span style=\"color: #3366ff;\">max<\/span> () - data. <span style=\"color: #3366ff;\">min<\/span> ())\n\n<span style=\"color: #008080;\">#view normalized values\n<\/span>data_norm\n\narray([[0. , 0.05172414, 0.10344828, 0.15517241, 0.17241379,\n        0.43103448, 0.5862069, 0.74137931, 0.77586207, 0.86206897,\n        0.89655172, 0.98275862, 1. ]])<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc815\uaddc\ud654\ub41c \ubc30\uc5f4\uc758 \uac01 \uac12\uc740 \uc774\uc81c 0\uacfc 1 \uc0ac\uc774\uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: Pandas DataFrame\uc758 \ubaa8\ub4e0 \ubcc0\uc218 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 Pandas DataFrame\uc758 \ubaa8\ub4e0 \ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#normalize values in every column\n<\/span>df_norm = (df-df. <span style=\"color: #3366ff;\">min<\/span> ())\/ (df. <span style=\"color: #3366ff;\">max<\/span> () - df. <span style=\"color: #3366ff;\">min<\/span> ())\n\n<span style=\"color: #008080;\">#view normalized DataFrame\n<\/span>df_norm\n\n        points assists rebounds\n0 0.764706 0.125 0.857143\n1 0.000000 0.375 0.428571\n2 0.176471 0.375 0.714286\n3 0.117647 0.625 0.142857\n4 0.411765 1.000 0.142857\n5 0.647059 0.625 0.000000\n6 0.764706 0.625 0.571429\n7 1.000000 0.000 1.000000\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uac01 \uc5f4\uc758 \uac01 \uac12\uc740 \uc774\uc81c 0\uacfc 1 \uc0ac\uc774\uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 3: Pandas DataFrame\uc758 \ud2b9\uc815 \ubcc0\uc218 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 Pandas DataFrame\uc5d0\uc11c \ud2b9\uc815 \ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">define columns to normalize<\/span>\nx = df. <span style=\"color: #3366ff;\">iloc<\/span> [:,0:2]\n\n<span style=\"color: #008080;\">#normalize values in first two columns only<\/span>\ndf. <span style=\"color: #3366ff;\">iloc<\/span> [:,0:2] = (xx. <span style=\"color: #3366ff;\">min<\/span> ())\/ (x. <span style=\"color: #3366ff;\">max<\/span> () - x. <span style=\"color: #3366ff;\">min<\/span> ())\n\n<span style=\"color: #008080;\">#view normalized DataFrame<\/span>\ndf\n\n\tpoints assists rebounds\n0 0.764706 0.125 11\n1 0.000000 0.375 8\n2 0.176471 0.375 10\n3 0.117647 0.625 6\n4 0.411765 1.000 6\n5 0.647059 0.625 5\n6 0.764706 0.625 9\n7 1.000000 0.000 12\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ucc98\uc74c \ub450 \uc5f4\uc758 \uac12\ub9cc \uc815\uaddc\ud654\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ub370\uc774\ud130 \uc815\uaddc\ud654\uc5d0 \ub300\ud55c \ucd94\uac00 \uc815\ubcf4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/0\u1100\u116a-1-\u1109\u1161\u110b\u1175\u110b\u1174-\u1103\u1166\u110b\u1175\u1110\u1165\u1105\u1173\u11af-\u110c\u1165\u11bc\u1100\u1172\u1112\u116a\/\" target=\"_blank\" rel=\"noopener\">0\uacfc 1 \uc0ac\uc774\uc758 \ub370\uc774\ud130\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/0\u110b\u1166\u1109\u1165-100-\u1109\u1161\u110b\u1175\u110b\u1174-\u1103\u1166\u110b\u1175\u1110\u1165\u1105\u1173\u11af-\u110c\u1165\u11bc\u1100\u1172\u1112\u116a\/\" target=\"_blank\" rel=\"noopener\">0\uc5d0\uc11c 100 \uc0ac\uc774\uc758 \ub370\uc774\ud130\ub97c \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u116d\u110c\u116e\u11ab\u1112\u116a-\u1103\u1162-\u110c\u1165\u11bc\u1100\u1172\u1112\u116a\/\" target=\"_blank\" rel=\"noopener\">\ud45c\uc900\ud654 \ub610\ub294 \uc815\uaddc\ud654: \ucc28\uc774\uc810\uc740 \ubb34\uc5c7\uc785\ub2c8\uae4c?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc885\uc885 \ud1b5\uacc4 \ubc0f \uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c\ub294 \uac12\uc758 \ubc94\uc704\uac00 0\uacfc 1 \uc0ac\uc774\uac00 \ub418\ub3c4\ub85d \ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud569\ub2c8\ub2e4 . \ubcc0\uc218\ub97c \uc815\uaddc\ud654\ud558\ub294 \uac00\uc7a5 \uc77c\ubc18\uc801\uc778 \uc774\uc720\ub294 \uc77c\uc885\uc758 \ub2e4\ubcc0\ub7c9 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uace0(\uc608: \uc5ec\ub7ec \uc608\uce21 \ubcc0\uc218\uc640 \ubc18\uc751 \ubcc0\uc218 \uac04\uc758 \uad00\uacc4\ub97c \uc774\ud574\ud558\uace0 \uc2f6\uace0) \uac01 \ubcc0\uc218\uac00 \ubd84\uc11d\uc5d0 \ub3d9\uc77c\ud558\uac8c \uae30\uc5ec\ud558\uae30\ub97c \uc6d0\ud560 \ub54c\uc785\ub2c8\ub2e4. \ubcc0\uc218\ub97c \ub2e4\uc591\ud55c \uaddc\ubaa8\ub85c \uce21\uc815\ud558\uba74 \ubd84\uc11d\uc5d0 \ub3d9\uc77c\ud558\uac8c \uae30\uc5ec\ud558\uc9c0 \uc54a\ub294 \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \ud55c \ubcc0\uc218\uc758 \uac12\uc774 0~100,000\uc774\uace0 [&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-2077","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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