{"id":1516,"date":"2023-07-26T01:35:25","date_gmt":"2023-07-26T01:35:25","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%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%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\/"},"modified":"2023-07-26T01:35:25","modified_gmt":"2023-07-26T01:35:25","slug":"%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%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","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%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%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\/","title":{"rendered":"Python\uc5d0\uc11c \ubaa9\ub85d\uc744 dataframe\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\uc885\uc885 Python\uc5d0\uc11c \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\uace0 \uc2f6\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788\ub3c4 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.html\" target=\"_blank\" rel=\"noopener\">pandas.DataFrame<\/a> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uba74 \uc774 \uc791\uc5c5\uc744 \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>pandas.DataFrame(data=None, index=None, columns=None, \u2026)<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>data:<\/strong> DataFrame\uc73c\ub85c \ubcc0\ud658\ud560 \ub370\uc774\ud130<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>index:<\/strong> \uacb0\uacfc DataFrame\uc5d0 \uc0ac\uc6a9\ud560 \uc778\ub371\uc2a4<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>columns:<\/strong> \uacb0\uacfc DataFrame\uc5d0 \uc0ac\uc6a9\ud560 \uc5f4 \ub808\uc774\ube14<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc758 \uc2e4\uc81c \uc0ac\uc6a9\uc5d0 \ub300\ud55c \uba87 \uac00\uc9c0 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc81c 1: \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa9\ub85d\uc744 Pandas DataFrame\uc73c\ub85c \ubcc0\ud658\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: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create list that contains points scored by 10 basketball players<\/span>\ndata = [4, 14, 17, 22, 26, 29, 33, 35, 35, 38]\n\n<span style=\"color: #008080;\">#convert list to DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data, columns=[' <span style=\"color: #008000;\">points<\/span> '])\n\n<span style=\"color: #008080;\">#view resulting DataFrame<\/span>\n<span style=\"color: #993300;\">print<\/span> (df)\n\n       points\n0 4\n1 14\n2 17\n3 22\n4 26\n5 29\n6 33\n7 35<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: \uc5ec\ub7ec \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \uc5ec\ub7ec \ubaa9\ub85d\uc744 Pandas DataFrame\uc73c\ub85c \ubcc0\ud658\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: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define lists\n<\/span><span style=\"color: #000000;\">points = [4, 14, 17, 22, 26, 29, 33, 35, 35, 38]\nrebounds = [1, 4, 4, 5, 8, 7, 5, 6, 9, 11]\n\n<span style=\"color: #008080;\">#convert lists into a single list\n<\/span>data = []\ndata. <span style=\"color: #3366ff;\">append<\/span> (dots)\ndata. <span style=\"color: #3366ff;\">append<\/span> (rebounds)\n\n<span style=\"color: #008000;\"><span style=\"color: #008080;\">#view new list<\/span>\n<span style=\"color: #000000;\">data<\/span>\n\n<span style=\"color: #000000;\">[[4, 14, 17, 22, 26, 29, 33, 35, 35, 38], [1, 4, 4, 5, 8, 7, 5, 6, 9, 11]]<\/span>\n<\/span>\n<span style=\"color: #008080;\">#convert list into DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data). <span style=\"color: #3366ff;\">transpose<\/span> ()\ndf. <span style=\"color: #3366ff;\">columns<\/span> =[' <span style=\"color: #008000;\">points<\/span> ', ' <span style=\"color: #008000;\">rebounds<\/span> ']\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span>df\n\n       rebound points\n0 4 1\n1 14 4\n2 17 4\n3 22 5\n4 26 8\n5 29 7\n6 33 5\n7 35 6\n8 35 9\n9 38 11\n<\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc81c 3: \ubaa9\ub85d \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa9\ub85d \ubaa9\ub85d\uc744 Pandas DataFrame\uc73c\ub85c \ubcc0\ud658\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: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define list of lists\n<\/span><span style=\"color: #000000;\">data = [[4, 1], [14, 4], [17, 4], [22, 5], [26, 8],\n        [29, 7], [33, 5], [35, 6], [35, 9], [38,11]]\n\n<span style=\"color: #008080;\">#convert list into DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data, columns=[' <span style=\"color: #008000;\">points<\/span> ', ' <span style=\"color: #008000;\">rebounds<\/span> '])\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span>df\n\n       rebound points\n0 4 1\n1 14 4\n2 17 4\n3 22 5\n4 26 8\n5 29 7\n6 33 5\n7 35 6\n8 35 9\n9 38 11<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uba74 \uacb0\uacfc DataFrame\uc758 \ud589\uacfc \uc5f4 \uc218\ub97c \ube60\ub974\uac8c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #107d3f;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#display number of rows and columns in DataFrame<\/span>\ndf.<\/span> <span style=\"color: #3366ff;\">shape\n<\/span><\/span><\/span>\n(10, 2)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc DataFrame\uc5d0\ub294 <strong>10\uac1c\uc758<\/strong> \ud589\uacfc <strong>2\uac1c\uc758<\/strong> \uc5f4\uc774 \uc788\ub294 \uac83\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub9ac\uace0 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uacb0\uacfc DataFrame\uc5d0\uc11c \uc5f4 \uc774\ub984\uc744 \uac80\uc0c9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #008080;\">#display column names of DataFrame<\/span>\nlist(df)\n<\/span>\n['points', 'rebounds']\n<\/strong><\/pre>\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 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\/\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 DataFrame\uc744 \ubaa9\ub85d\uc73c\ub85c \ubcc0\ud658\ud558\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 \uc0ac\uc804\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1106\u116e\u11ab\u110c\u1161\u110b\u1167\u11af\u110b\u1173\u11af-\u1107\u116e\u1103\u1169\u11bc-\u1111\u1162\u11ab\u1103\u1165\u1105\u1169-\u1107\u1167\u11ab\u1112\u116a\u11ab\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \ubb38\uc790\uc5f4\uc744 \ubd80\ub3d9 \uc18c\uc218\uc810\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc885\uc885 Python\uc5d0\uc11c \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\uace0 \uc2f6\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ud589\ud788\ub3c4 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 pandas.DataFrame \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uba74 \uc774 \uc791\uc5c5\uc744 \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. pandas.DataFrame(data=None, index=None, columns=None, \u2026) \uae08: data: DataFrame\uc73c\ub85c \ubcc0\ud658\ud560 \ub370\uc774\ud130 index: \uacb0\uacfc DataFrame\uc5d0 \uc0ac\uc6a9\ud560 \uc778\ub371\uc2a4 columns: \uacb0\uacfc DataFrame\uc5d0 \uc0ac\uc6a9\ud560 \uc5f4 \ub808\uc774\ube14 \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc758 \uc2e4\uc81c \uc0ac\uc6a9\uc5d0 \ub300\ud55c \uba87 \uac00\uc9c0 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc608\uc81c 1: \ubaa9\ub85d\uc744 [&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-1516","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 \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc5ec\ub7ec \uc608\uc81c\ub97c \ud1b5\ud574 Python\uc5d0\uc11c \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/\u1103\u1166\u110b\u1175\u1110\u1165-\u1111\u1173\u1105\u1166\u110b\u1175\u11b7-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1166\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python\uc5d0\uc11c \ubaa9\ub85d\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95 - Statorials\" \/>\n<meta property=\"og:description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc5ec\ub7ec \uc608\uc81c\ub97c \ud1b5\ud574 Python\uc5d0\uc11c \ubaa9\ub85d\uc744 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