{"id":1822,"date":"2023-07-24T20:30:21","date_gmt":"2023-07-24T20:30:21","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%ad%e1%84%8c%e1%85%ae%e1%86%ab%e1%84%92%e1%85%aa\/"},"modified":"2023-07-24T20:30:21","modified_gmt":"2023-07-24T20:30:21","slug":"%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%ad%e1%84%8c%e1%85%ae%e1%86%ab%e1%84%92%e1%85%aa","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%ad%e1%84%8c%e1%85%ae%e1%86%ab%e1%84%92%e1%85%aa\/","title":{"rendered":"Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ud45c\uc900\ud654\ud558\ub294 \ubc29\ubc95: \uc608\uc81c \ud3ec\ud568"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub370\uc774\ud130\uc138\ud2b8\ub97c <strong>\ud45c\uc900\ud654\ud55c\ub2e4\ub294<\/strong> \uac83\uc740 \ub370\uc774\ud130\uc138\ud2b8\uc758 \ubaa8\ub4e0 \uac12\uc744 \ud3c9\uade0\uac12\uc774 0, \ud45c\uc900\ud3b8\ucc28\uac00 1\uc774 \ub418\ub3c4\ub85d \uc870\uc815\ud558\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac12\uc744 \uc815\uaddc\ud654\ud558\ub824\uba74 \ub2e4\uc74c \uacf5\uc2dd\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>x <sub>\uc0c8\ub85c\uc6b4<\/sub> = (x <sub>i<\/sub> \u2013 <span style=\"text-decoration: overline;\">x<\/span> ) \/ s<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\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><span style=\"text-decoration: overline;\">x<\/span><\/strong> : \ud45c\ubcf8\uc758 \uc758\ubbf8<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>s<\/strong> : \ud45c\ubcf8\uc758 \ud45c\uc900\ud3b8\ucc28<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c pandas DataFrame\uc758 \ubaa8\ub4e0 \uc5f4\uc744 \ube60\ub974\uac8c \uc815\uaddc\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>(df- <span style=\"color: #3366ff;\">df.mean<\/span> ())\/df. <span style=\"color: #3366ff;\">std<\/span> ()\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uad6c\ubb38\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: \ubaa8\ub4e0 DataFrame \uc5f4 \ud45c\uc900\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 Pandas DataFrame\uc758 \ubaa8\ub4e0 \uc5f4\uc744 \ud45c\uc900\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">y<\/span> ': [8, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">x1<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">x2<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' <span style=\"color: #ff0000;\">x3<\/span> ': [2, 2, 3, 2, 5, 5, 7, 9]})\n\n<span style=\"color: #008080;\">#view data frame\n<\/span>df\n\n\ty x1 x2 x3\n0 8 5 11 2\n1 12 7 8 2\n2 15 7 10 3\n3 14 9 6 2\n4 19 12 6 5\n5 23 9 5 5\n6 25 9 9 7\n7 29 4 12 9\n\n<span style=\"color: #008080;\">#standardize the values in each column\n<\/span>df_new = (df- <span style=\"color: #3366ff;\">df.mean<\/span> ())\/df. <span style=\"color: #3366ff;\">std<\/span> ()\n\n<span style=\"color: #008080;\">#view new data frame\n<\/span>df_new\n\n\t        y x1 x2 x3\n0 -1.418032 -1.078639 1.025393 -0.908151\n1 -0.857822 -0.294174 -0.146485 -0.908151\n2 -0.437664 -0.294174 0.634767 -0.525772\n3 -0.577717 0.490290 -0.927736 -0.908151\n4 0.122546 1.666987 -0.927736 0.238987\n5 0.682756 0.490290 -1.318362 0.238987\n6 0.962861 0.490290 0.244141 1.003746\n7 1.523071 -1.470871 1.416019 1.768505<\/b><\/pre>\n<p> <span style=\"color: #000000;\">\uac01 \uc5f4\uc758 \ud3c9\uade0\uacfc \ud45c\uc900\ud3b8\ucc28\uac00 \uac01\uac01 0\uacfc 1\uc778 \uac83\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008080;\">#view mean of each column\n<\/span>df_new. <span style=\"color: #3366ff;\">mean<\/span> ()\n\ny 0.000000e+00\nx1 2.775558e-17\nx2 -4.163336e-17\nx3 5.551115e-17\ndtype:float64\n\n<span style=\"color: #008080;\">#view standard deviation of each column\n<\/span>df_new. <span style=\"color: #3366ff;\">std<\/span> ()\n\ny 1.0\nx1 1.0\nx2 1.0\nx3 1.0\ndtype:float64\n<\/b><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \ud2b9\uc815 DataFrame \uc5f4 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub54c\ub85c\ub294 DataFrame\uc758 \ud2b9\uc815 \uc5f4\ub9cc \uc815\uaddc\ud654\ud558\uace0 \uc2f6\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4, \ub9ce\uc740 <a href=\"https:\/\/statorials.org\/ko\/\u1110\u1169\u11bc\u1100\u1168\u1112\u1161\u11a8\u110b\u1173\u11ab-\u1100\u1161\u11ab\u1103\u1161\u11ab\u1112\u1161\u1100\u1169-\u110c\u1175\u11a8\u110c\u1165\u11b8\u110c\u1165\u11a8\u110b\u1175\u11ab-\u1107\u1161\u11bc\u1107\u1165\u11b8\u110b\u1173\u1105\u1169-\u1100\u1162\u1102\u1167\u11b7\u110b\u1173\u11af-\u1109\u1165\u11af\u1106\u1167\u11bc\u1112\u1161\u1106\u1173\u1105\u1169-\u1110\u1169\u11bc\u1100\u1168\u1105\u1173\u11af-\u1103\u1165-\u1109\u1171\u11b8\u1100\u1166-\u1107\u1162\u110b\u116e\u11af-\u1109\u116e-\u110b\u1175\u11bb\u1109\u1173\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\uae30\uacc4 \ud559\uc2b5 \uc54c\uace0\ub9ac\uc998<\/a> \uc758 \uacbd\uc6b0 \ud2b9\uc815 \ubaa8\ub378\uc744 \ub370\uc774\ud130\uc5d0 \ub9de\ucd94\uae30 \uc804\uc5d0 \uc608\uce21 \ubcc0\uc218\ub9cc \ud45c\uc900\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 Pandas DataFrame\uc758 \ud2b9\uc815 \uc5f4\uc744 \ud45c\uc900\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">y<\/span> ': [8, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">x1<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">x2<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' <span style=\"color: #ff0000;\">x3<\/span> ': [2, 2, 3, 2, 5, 5, 7, 9]})\n\n<span style=\"color: #008080;\">#view data frame\n<\/span>df\n\n\ty x1 x2 x3\n0 8 5 11 2\n1 12 7 8 2\n2 15 7 10 3\n3 14 9 6 2\n4 19 12 6 5\n5 23 9 5 5\n6 25 9 9 7\n7 29 4 12 9\n\n<span style=\"color: #008080;\">#define predictor variable columns<\/span>\ndf_x = df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]\n\n<span style=\"color: #008080;\">#standardize the values for each predictor variable\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ',' <span style=\"color: #ff0000;\">x2<\/span> ',' <span style=\"color: #ff0000;\">x3<\/span> ']] = (df_x- <span style=\"color: #3366ff;\">df_x.mean<\/span> ())\/df_x. <span style=\"color: #3366ff;\">std<\/span> ()\n\n<span style=\"color: #008080;\">#view new data frame\n<\/span>df\n\n         y x1 x2 x3\n0 8 -1.078639 1.025393 -0.908151\n1 12 -0.294174 -0.146485 -0.908151\n2 15 -0.294174 0.634767 -0.525772\n3 14 0.490290 -0.927736 -0.908151\n4 19 1.666987 -0.927736 0.238987\n5 23 0.490290 -1.318362 0.238987\n6 25 0.490290 0.244141 1.003746\n7 29 -1.470871 1.416019 1.768505<\/b><\/pre>\n<p> <span style=\"color: #000000;\">\uc5f4 &#8220;y&#8221;\ub294 \ubcc0\uacbd\ub418\uc9c0 \uc54a\uc740 \uc0c1\ud0dc\ub85c \uc720\uc9c0\ub418\uc9c0\ub9cc &#8220;x1&#8221;, &#8220;x2&#8221; \ubc0f &#8220;x3&#8221; \uc5f4\uc740 \ubaa8\ub450 \ud45c\uc900\ud654\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\uce21 \ubcc0\uc218\uc758 \uac01 \uc5f4\uc758 \ud3c9\uade0\uacfc \ud45c\uc900 \ud3b8\ucc28\uac00 \uac01\uac01 0\uacfc 1\uacfc \uac19\uc740\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008080;\">#view mean of each predictor variable column\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]. <span style=\"color: #3366ff;\">mean<\/span> ()\n\nx1 2.775558e-17\nx2 -4.163336e-17\nx3 5.551115e-17\ndtype:float64\n\n<span style=\"color: #008080;\">#view standard deviation of each predictor variable column\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]. <span style=\"color: #3366ff;\">std<\/span> ()\n\nx1 1.0\nx2 1.0\nx3 1.0\ndtype:float64<\/b><\/pre>\n<h3> <strong><span style=\"color: #000000;\">\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/span><\/strong><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111\u1173\u1105\u1166\u110b\u1175\u11b7-\u110b\u1167\u11af-\u110c\u1165\u11bc\u1100\u1172\u1112\u116a\/\" target=\"_blank\" rel=\"noopener\">Pandas DataFrame\uc758 \uc5f4\uc744 \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u110b\u1175\u1109\u1161\u11bc\u1100\u1161\u11b9-\u110c\u1166\u1100\u1165-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \uc774\uc0c1\uac12\uc744 \uc81c\uac70\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>\ub370\uc774\ud130\uc138\ud2b8\ub97c \ud45c\uc900\ud654\ud55c\ub2e4\ub294 \uac83\uc740 \ub370\uc774\ud130\uc138\ud2b8\uc758 \ubaa8\ub4e0 \uac12\uc744 \ud3c9\uade0\uac12\uc774 0, \ud45c\uc900\ud3b8\ucc28\uac00 1\uc774 \ub418\ub3c4\ub85d \uc870\uc815\ud558\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac12\uc744 \uc815\uaddc\ud654\ud558\ub824\uba74 \ub2e4\uc74c \uacf5\uc2dd\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. x \uc0c8\ub85c\uc6b4 = (x i \u2013 x ) \/ s \uae08: x i : \ub370\uc774\ud130\uc138\ud2b8\uc758 i\ubc88\uc9f8 \uac12 x : \ud45c\ubcf8\uc758 \uc758\ubbf8 s : \ud45c\ubcf8\uc758 \ud45c\uc900\ud3b8\ucc28 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c pandas DataFrame\uc758 \ubaa8\ub4e0 \uc5f4\uc744 \ube60\ub974\uac8c [&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-1822","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>Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ud45c\uc900\ud654\ud558\ub294 \ubc29\ubc95: \uc608\uc81c \ud3ec\ud568<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c 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