{"id":3126,"date":"2023-07-19T02:04:14","date_gmt":"2023-07-19T02:04:14","guid":{"rendered":"https:\/\/statorials.org\/ko\/pandas-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%89%e1%85%a6%e1%84%90%e1%85%b3\/"},"modified":"2023-07-19T02:04:14","modified_gmt":"2023-07-19T02:04:14","slug":"pandas-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%89%e1%85%a6%e1%84%90%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/pandas-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%89%e1%85%a6%e1%84%90%e1%85%b3\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc0d8\ud50c \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \uc561\uc138\uc2a4\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \uc2e4\ud589\ud558\uace0 \uc5f0\uc2b5\ud558\uae30 \uc704\ud574 Pandas\uc758 \uc0d8\ud50c \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \uc561\uc138\uc2a4\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788 \ub0b4\uc7a5\ub41c <strong>\ud14c\uc2a4\ud2b8<\/strong> \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc0d8\ud50c Pandas \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \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 \uc22b\uc790 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130\uc138\ud2b8 \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa8\ub4e0 \uc22b\uc790 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130\uc138\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create sample dataset<\/span>\ndf1 = pd. <span style=\"color: #3366ff;\">util<\/span> . <span style=\"color: #3366ff;\">testing<\/span> . <span style=\"color: #3366ff;\">makeDataFrame<\/span> ()\n\n<span style=\"color: #008080;\">#view dimensions of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df1.shape<\/span> )\n\n(30, 4)\n\n<span style=\"color: #008080;\">#view first five rows of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df1.head<\/span> ())\n\n                   ABCD\ns8tpz0W5mF -0.751223 0.956338 -0.441847 0.695612\nCXQ9YhLhk8 -0.210881 -0.231347 -0.227672 -0.616171\nKAbcor6sQK 0.727880 0.128638 -0.989993 1.094069\nIH3bptMpdb -1.599723 1.570162 -0.221688 2.194936\ngar9ZxBTrH 0.025171 -0.446555 0.169873 -1.583553\n<\/b><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uae30\ubcf8\uc801\uc73c\ub85c <strong>makeDataFrame()<\/strong> \ud568\uc218\ub294 \ubaa8\ub4e0 \uc5f4\uc774 \uc22b\uc790\uc778 30\uac1c\uc758 \ud589\uacfc 4\uac1c\uc758 \uc5f4\uc774 \uc788\ub294 pandas DataFrame\uc744 \ub9cc\ub4ed\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: \ud63c\ud569 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130 \uc138\ud2b8 \uc0dd\uc131<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa8\ub4e0 \uc22b\uc790 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130\uc138\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create sample dataset<\/span>\ndf2 = pd. <span style=\"color: #3366ff;\">util<\/span> . <span style=\"color: #3366ff;\">testing<\/span> . <span style=\"color: #3366ff;\">makeMixedDataFrame<\/span> ()\n\n<span style=\"color: #008080;\">#view dimensions of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df2.shape<\/span> )\n\n(5, 4)\n\n<span style=\"color: #008080;\">#view first five rows of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df2.head<\/span> ())\n\n     ABCD\n0 0.0 0.0 foo1 2009-01-01\n1 1.0 1.0 foo2 2009-01-02\n2 2.0 0.0 foo3 2009-01-05\n3 3.0 1.0 foo4 2009-01-06\n4 4.0 0.0 foo5 2009-01-07\n<\/b><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uae30\ubcf8\uc801\uc73c\ub85c <strong>makeMixedDataFrame()<\/strong> \ud568\uc218\ub294 \uc5f4\uc774 \ub2e4\uc591\ud55c \ub370\uc774\ud130 \uc720\ud615\uc778 5\uac1c\uc758 \ud589\uacfc 4\uac1c\uc758 \uc5f4\uc774 \uc788\ub294 pandas DataFrame\uc744 \ub9cc\ub4ed\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1106\u1169\u1103\u1173\u11ab-\u110b\u1167\u11af\u110b\u1173\u11af-dtype\u110b\u1173\u1105\u1169-\u1112\u116a\u11a8\u110b\u1175\u11ab\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\uac01 \uc5f4\uc758 \ub370\uc774\ud130 \uc720\ud615\uc744<\/a> \ud45c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><b><span style=\"color: #008080;\">#display data type of each column\n<span style=\"color: #000000;\">df2. <span style=\"color: #3366ff;\">dtypes\n\n<span style=\"color: #000000;\">A float64\nB float64\nC object\nD datetime64[ns]\ndtype:object<\/span><\/span><\/span>\n<\/span><\/b><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">A \uc5f4\uc740 \uc22b\uc790\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">B \uc5f4\uc740 \uc22b\uc790\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">C \uc5f4\uc740 \ubb38\uc790\uc5f4\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">D \uc5f4\uc740 \ub0a0\uc9dc\uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 3: \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 Pandas \ub370\uc774\ud130 \uc138\ud2b8 \uc0dd\uc131<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub2e4\uc591\ud55c \uc5f4\uc5d0 \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 Pandas \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create sample dataset<\/span>\ndf3 = pd. <span style=\"color: #3366ff;\">util<\/span> . <span style=\"color: #3366ff;\">testing<\/span> . <span style=\"color: #3366ff;\">makeMissingDataFrame<\/span> ()\n\n<span style=\"color: #008080;\">#view dimensions of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df3.shape<\/span> )\n\n(30, 4)\n\n<span style=\"color: #008080;\">#view first five rows of dataset<\/span>\n<span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df3.head<\/span> ())\n\n                   ABCD\nYgAQaNaGfG 0.444376 -2.264920 1.117377 -0.087507\nJoT4KxJeHd 1.913939 1.287006 -0.331315 -0.392949\ntyrA2P6wz3 NaN 2.988521 0.399583 0.095831\n1qvPc9DU1t 0.028716 1.311452 -0.237756 -0.150362\n3aAXYtXjIO -1.069339 0.332067 0.204074 NaN\n<\/b><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uae30\ubcf8\uc801\uc73c\ub85c <strong>makeMissingDataFrame()<\/strong> \ud568\uc218\ub294 \uc11c\ub85c \ub2e4\ub978 \uc5f4\uc5d0 \ub204\ub77d\ub41c \uac12(NaN)\uc774 \uc788\ub294 30\uac1c\uc758 \ud589\uacfc 4\uac1c\uc758 \uc5f4\uc774 \uc788\ub294 pandas DataFrame\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \uae30\ub2a5\uc740 \uc2e4\uc81c \ub370\uc774\ud130\uc138\ud2b8\uc5d0\uc11c \ud754\ud788 \ubc1c\uc0dd\ud558\ub294 \uacb0\uce21\uac12\uc774 \uc788\ub294 \ub370\uc774\ud130\uc138\ud2b8\ub85c \uc791\uc5c5\ud560 \uc218 \uc788\uae30 \ub54c\ubb38\uc5d0 \ud2b9\ud788 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong><span style=\"color: #000000;\">\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/span><\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\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\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1106\u116e\u110c\u1161\u11a8\u110b\u1171-\u1103\u1166\u110b\u1175\u1110\u1165\u1105\u1173\u11af-\u1109\u1162\u11bc\u1109\u1165\u11bc\u1112\u1161\u11b8\u1102\u1175\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">\uc784\uc758\uc758 \ub370\uc774\ud130\ub85c Pandas DataFrame\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><br \/> <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\">Pandas\uc5d0\uc11c \ud589\uc744 \ubb34\uc791\uc704\ub85c \uc0d8\ud50c\ub9c1\ud558\ub294 \ubc29\ubc95<\/a><br \/> Pandas DataFrame\uc5d0\uc11c \ud589\uc744 \uc11e\ub294 \ubc29\ubc95<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \uc2e4\ud589\ud558\uace0 \uc5f0\uc2b5\ud558\uae30 \uc704\ud574 Pandas\uc758 \uc0d8\ud50c \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \uc561\uc138\uc2a4\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ud589\ud788 \ub0b4\uc7a5\ub41c \ud14c\uc2a4\ud2b8 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc0d8\ud50c Pandas \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608\uc2dc 1: \ubaa8\ub4e0 \uc22b\uc790 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130\uc138\ud2b8 \ub9cc\ub4e4\uae30 \ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa8\ub4e0 \uc22b\uc790 \uc5f4\uc774 \ud3ec\ud568\ub41c Pandas \ub370\uc774\ud130\uc138\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. import pandas as pd [&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-3126","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\uc5d0\uc11c \uc0d8\ud50c \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \uc561\uc138\uc2a4\ud558\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec \ud50c\ub808\uc774\ud560 Pandas\uc758 \uc0d8\ud50c \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \uc561\uc138\uc2a4\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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