{"id":2379,"date":"2023-07-22T12:42:25","date_gmt":"2023-07-22T12:42:25","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b5%e1%86%af%e1%84%80%e1%85%a9-%e1%84%82%e1%85%a5%e1%86%b2%e1%84%8b%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5\/"},"modified":"2023-07-22T12:42:25","modified_gmt":"2023-07-22T12:42:25","slug":"%e1%84%80%e1%85%b5%e1%86%af%e1%84%80%e1%85%a9-%e1%84%82%e1%85%a5%e1%86%b2%e1%84%8b%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b5%e1%86%af%e1%84%80%e1%85%a9-%e1%84%82%e1%85%a5%e1%86%b2%e1%84%8b%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5\/","title":{"rendered":"Pandas: dataframe\uc758 \ubaa8\uc591\uc744 \uae34 \uac83\uc5d0\uc11c \ub113\uc740 \uac83\uc73c\ub85c \ubc14\uafb8\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc744 \uae34 \ud615\uc2dd\uc5d0\uc11c \ub113\uc740 \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df = pd. <span style=\"color: #3366ff;\">pivot<\/span> (df, index=' <span style=\"color: #ff0000;\">col1<\/span> ', columns=' <span style=\"color: #ff0000;\">col2<\/span> ', values=' <span style=\"color: #ff0000;\">col3<\/span> ')\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \uc2dc\ub098\ub9ac\uc624\uc5d0\uc11c\ub294 <strong>col1\uc774<\/strong> \uc778\ub371\uc2a4\uac00 \ub418\uace0, <strong>col2\ub294<\/strong> \uc5f4\uc774 \ub418\uba70, <strong>col3\uc740<\/strong> DataFrame \ub0b4\ubd80\uc758 \uac12\uc73c\ub85c \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608: Pandas DataFrame\uc758 \ubaa8\uc591\uc744 \uae34 \uac83\uc5d0\uc11c \ub113\uc740 \uac83\uc73c\ub85c \ubcc0\uacbd<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \uae34 \ud615\uc2dd\uc758 pandas 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: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#create DataFrame in long format\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' <span style=\"color: #ff0000;\">player<\/span> ': [1, 2, 3, 4, 1, 2, 3, 4],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [11, 8, 10, 6, 12, 5, 9, 4]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tteam player points\n0 to 1 11\n1 to 2 8\n2 to 3 10\n3 to 4 6\n4 B 1 12\n5 B 2 5\n6 B 3 9\n7 B 4 4\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc774 DataFrame\uc744 \uae34 \ud615\uc2dd\uc5d0\uc11c \ub113\uc740 \ud615\uc2dd\uc73c\ub85c \ubcc0\uacbd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#reshape DataFrame from long format to wide format\n<span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">pivot<\/span> (df, index=' <span style=\"color: #ff0000;\">team<\/span> ', columns=' <span style=\"color: #ff0000;\">player<\/span> ', values=' <span style=\"color: #ff0000;\">points<\/span> ')\n<\/span>\n#view updated DataFrame\n<span style=\"color: #000000;\">df\n\nplayer 1 2 3 4\nteam\t\t\t\t\nA 11 8 10 6\nB 12 5 9 4<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">DataFrame\uc740 \uc774\uc81c \uc640\uc774\ub4dc \ud615\uc2dd\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">DataFrame \ub0b4\ubd80\uc758 \uac12\uc740 &#8220;team&#8221;\uc744 \uc778\ub371\uc2a4 \uc5f4\ub85c, &#8220;player&#8221;\ub97c \uc5f4\ub85c, &#8220;points&#8221;\ub97c \uac12\uc73c\ub85c \uc0ac\uc6a9\ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc6d0\ud558\ub294 \uacbd\uc6b0 \ub300\uc2e0 &#8220;player&#8221;\ub97c \uc778\ub371\uc2a4 \uc5f4\ub85c \uc0ac\uc6a9\ud558\uace0 &#8220;team&#8221;\uc744 \uc5f4\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#reshape DataFrame from long format to wide format\n<span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">pivot<\/span> (df, index=' <span style=\"color: #ff0000;\">player<\/span> ', columns=' <span style=\"color: #ff0000;\">team<\/span> ', values=' <span style=\"color: #ff0000;\">points<\/span> ')\n<\/span>\n#view updated DataFrame\n<span style=\"color: #000000;\">df\n\nteam A B\nplayer\t\t\n1 11 12\n2 8 5\n3 10 9\n4 6 4\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 DataFrame\ub3c4 \uc640\uc774\ub4dc \ud615\uc2dd\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.pivot.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> Pandas <strong>\ud53c\ubc97()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\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\/\u1102\u1165\u11b2\u110b\u1173\u11ab-\u1111\u1161\u11ab\u1103\u1161\u110b\u1166\u1109\u1165-\u1100\u1175\u11ab-\u1111\u1161\u11ab\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">Pandas: DataFrame\uc758 \ubaa8\uc591\uc744 \ub113\uc740 \uac83\uc5d0\uc11c \uae34 \uac83\uc73c\ub85c \ubc14\uafb8\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111\u1173\u1105\u1166\u110b\u1175\u11b7\u110b\u1166-\u110c\u116e\u11af\u110b\u1173\u11af-\u110e\u116e\u1100\u1161\u1112\u1161\u11b8\u1102\u1175\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">Pandas DataFrame\uc5d0 \ud589\uc744 \ucd94\uac00\ud558\ub294 \ubc29\ubc95<\/a><br \/> Pandas DataFrame\uc5d0 \uc5f4\uc744 \ucd94\uac00\ud558\ub294 \ubc29\ubc95<br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u110b\u1167\u11af\u110b\u1174-\u1110\u1173\u11a8\u110c\u1165\u11bc-\u1100\u1161\u11b9\u110b\u1173\u11af-\u1100\u1168\u1109\u1161\u11ab\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas DataFrame\uc5d0\uc11c \ud2b9\uc815 \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc744 \uae34 \ud615\uc2dd\uc5d0\uc11c \ub113\uc740 \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df = pd. pivot (df, index=&#8217; col1 &#8216;, columns=&#8217; col2 &#8216;, values=&#8217; col3 &#8216;) \uc774 \uc2dc\ub098\ub9ac\uc624\uc5d0\uc11c\ub294 col1\uc774 \uc778\ub371\uc2a4\uac00 \ub418\uace0, col2\ub294 \uc5f4\uc774 \ub418\uba70, col3\uc740 DataFrame \ub0b4\ubd80\uc758 \uac12\uc73c\ub85c \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608: Pandas DataFrame\uc758 \ubaa8\uc591\uc744 \uae34 \uac83\uc5d0\uc11c \ub113\uc740 [&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-2379","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: DataFrame\uc744 \uae34 \ud615\ud0dc\uc5d0\uc11c \ub113\uc740 \ud615\ud0dc\ub85c \uc7ac\uad6c\uc131\ud558\ub294 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