{"id":2507,"date":"2023-07-21T23:16:20","date_gmt":"2023-07-21T23:16:20","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%b4-%e1%84%89%e1%85%a6%e1%86%ab%e1%84%90%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5\/"},"modified":"2023-07-21T23:16:20","modified_gmt":"2023-07-21T23:16:20","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%b4-%e1%84%89%e1%85%a6%e1%86%ab%e1%84%90%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5","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%b4-%e1%84%89%e1%85%a6%e1%86%ab%e1%84%90%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5\/","title":{"rendered":"Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\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>\uc911\uc559\uc5d0 \ubc30\uce58\ud55c\ub2e4\ub294<\/strong> \uac83\uc740 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac01 \uac1c\ubcc4 <a href=\"https:\/\/statorials.org\/ko\/\u1110\u1169\u11bc\u1100\u1168\u110b\u1166\u1109\u1165\u110b\u1174-\u1100\u116a\u11ab\u110e\u1161\u11af\/\" target=\"_blank\" rel=\"noopener\">\uad00\uce21\uce58<\/a> \uc758 <a href=\"https:\/\/statorials.org\/ko\/\u110c\u116e\u11bc\u1109\u1175\u11b7-\u1100\u1167\u11bc\u1112\u1163\u11bc\u110b\u1173\u11af-\u110e\u1173\u11a8\u110c\u1165\u11bc\/\" target=\"_blank\" rel=\"noopener\">\ud3c9\uade0\uac12\uc744<\/a> \ube7c\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\ud558\uba74 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ud3c9\uade0\uac12\uc740 0\uc774 \ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\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\uc758 \uac12\uc744 \uc911\uc559\uc5d0 \ubc30\uce58<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 NumPy \ubc30\uc5f4\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/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<\/span>\ndata = np. <span style=\"color: #3366ff;\">array<\/span> ([4, 6, 9, 13, 14, 17, 18, 19, 19, 21])\n\n<span style=\"color: #008080;\">#display mean of array<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">data.mean<\/span> ())\n\n14.0<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uac01 \uac1c\ubcc4 \uad00\ucc30\uc5d0\uc11c \ud3c9\uade0 \ubc30\uc5f4 \uac12\uc744 \ube7c\ub294 <a href=\"https:\/\/statorials.org\/ko\/\u1103\u1175\u110c\u1175\u1110\u1165\u11af-\u110f\u1161\u1103\u1173\/\" target=\"_blank\" rel=\"noopener\">\ud568\uc218\ub97c<\/a> \uc815\uc758\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create function to data center\n<span style=\"color: #000000;\">center_function = <span style=\"color: #008000;\">lambda<\/span> x: x - x. <span style=\"color: #3366ff;\">mean<\/span> ()<\/span>\n\n#apply function to original NumPy array\n<span style=\"color: #000000;\">data_centered = center_function(data)\n<\/span>\n#view updated Array\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">print<\/span> (data_centered)\n\narray([-10., -8., -5., -1., 0., 3., 4., 5., 5., 7.])\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc \uac12\uc740 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uc911\uc2ec \uac12\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc6d0\ub798 \ud14c\uc774\ube14\uc758 \ud3c9\uade0\uc774 14\uc600\uc73c\ubbc0\ub85c \uc774 \ud568\uc218\ub294 \ub2e8\uc21c\ud788 \uc6d0\ub798 \ud14c\uc774\ube14\uc758 \uac01 \uac1c\ubcc4 \uac12\uc5d0\uc11c 14\ub97c \ube8d\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uc911\uc559 \ubc30\uc5f4\uc758 \uccab \ubc88\uc9f8 \uac12 = 4 \u2013 14 = <strong>-10<\/strong><\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc911\uc559 \ubc30\uc5f4\uc758 \ub450 \ubc88\uc9f8 \uac12 = 6 \u2013 14 = <strong>-8<\/strong><\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc911\uc559 \ubc30\uc5f4\uc758 \uc138 \ubc88\uc9f8 \uac12 = 9 \u2013 14 = <strong>-5<\/strong><\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub4f1\ub4f1.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub610\ud55c \uc911\uc559 \ud14c\uc774\ube14\uc758 \ud3c9\uade0\uc774 0\uc778\uc9c0 \ud655\uc778\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#display mean of centered array<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">data_centered.mean<\/span> ())\n\n0.0<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: Pandas DataFrame\uc758 \uc5f4\uc744 \uc911\uc559\uc5d0 \ubc30\uce58<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/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\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">x<\/span> ': [1, 4, 5, 6, 6, 8, 9],\n                   ' <span style=\"color: #ff0000;\">y<\/span> ': [7, 7, 8, 8, 8, 9, 12],\n                   ' <span style=\"color: #ff0000;\">z<\/span> ': [3, 3, 4, 4, 6, 7, 7]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   X Y Z\n0 1 7 3\n1 4 7 3\n2 5 8 4\n3 6 8 4\n4 6 8 6\n5 8 9 7\n6 9 12 7<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">pandas <strong>apply()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \uc5f4 \uac12\uc744 \uc911\uc559\uc5d0 \ubc30\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#center the values in each column of the DataFrame<\/span>\ndf_centered = df. <span style=\"color: #3366ff;\">apply<\/span> ( <span style=\"color: #008000;\">lambda<\/span> x: <span style=\"color: #3366ff;\">xx.mean<\/span> ())\n\n<span style=\"color: #008080;\">#view centered DataFrame<\/span>\n<span style=\"color: #008000;\">print<\/span> (df_centered)\n\n\t        X Y Z\n0 -4.571429 -1.428571 -1.857143\n1 -1.571429 -1.428571 -1.857143\n2 -0.571429 -0.428571 -0.857143\n3 0.428571 -0.428571 -0.857143\n4 0.428571 -0.428571 1.142857\n5 2.428571 0.571429 2.142857\n6 3.428571 3.571429 2.142857 \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uadf8\ub7f0 \ub2e4\uc74c \uac01 \uc5f4\uc758 \ud3c9\uade0 \uac12\uc774 0\uc778\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#display mean of each column in the DataFrame<\/span>\ndf_centered. <span style=\"color: #3366ff;\">mean<\/span> ()\n\nx 2.537653e-16\ny-2.537653e-16\nz 3.806479e-16\ndtype:float64\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc5f4 \ud3c9\uade0\uc740 \uacfc\ud559\uc801 \ud45c\uae30\ubc95\uc73c\ub85c \ud45c\uc2dc\ub418\uc9c0\ub9cc \uac01 \uac12\uc740 \uae30\ubcf8\uc801\uc73c\ub85c 0\uc785\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 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1174-\u110c\u116e\u11bc\u1100\u1161\u11ab-\u110f\u1173\u1100\u1175\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \uc808\uc0ac \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u110c\u1166\u1100\u1169\u11b8-\u110b\u1169\u1105\u1172-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1173\u11af-\u110b\u1174\u1106\u1175\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \ud3c9\uade0 \uc81c\uacf1 \uc624\ucc28(MSE)\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1109\u1165\u11ab\u1110\u1162\u11a8\u1103\u116c\u11ab-\u110b\u1167\u11af\u110b\u1173\u11af-\u1111\u1167\u11bc\u1100\u1172\u11ab\u1112\u116a\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \uc120\ud0dd\ud55c \uc5f4\uc758 \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\ud55c\ub2e4\ub294 \uac83\uc740 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac01 \uac1c\ubcc4 \uad00\uce21\uce58 \uc758 \ud3c9\uade0\uac12\uc744 \ube7c\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\ud558\uba74 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ud3c9\uade0\uac12\uc740 0\uc774 \ub429\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc911\uc559\uc5d0 \ubc30\uce58\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608\uc2dc 1: NumPy \ubc30\uc5f4\uc758 \uac12\uc744 \uc911\uc559\uc5d0 \ubc30\uce58 \ub2e4\uc74c\uacfc \uac19\uc740 NumPy \ubc30\uc5f4\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4. import numpy as np #create NumPy array data = np. 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