{"id":3274,"date":"2023-07-18T08:17:47","date_gmt":"2023-07-18T08:17:47","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%92%e1%85%a1%e1%86%b8%e1%84%80%e1%85%a8-%e1%84%8b%e1%85%a1%e1%84%85%e1%85%a2-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%91%e1%85%b5%e1%84%87%e1%85%a5%e1%86%ba-%e1%84%90%e1%85%a6\/"},"modified":"2023-07-18T08:17:47","modified_gmt":"2023-07-18T08:17:47","slug":"%e1%84%92%e1%85%a1%e1%86%b8%e1%84%80%e1%85%a8-%e1%84%8b%e1%85%a1%e1%84%85%e1%85%a2-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%91%e1%85%b5%e1%84%87%e1%85%a5%e1%86%ba-%e1%84%90%e1%85%a6","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%92%e1%85%a1%e1%86%b8%e1%84%80%e1%85%a8-%e1%84%8b%e1%85%a1%e1%84%85%e1%85%a2-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%91%e1%85%b5%e1%84%87%e1%85%a5%e1%86%ba-%e1%84%90%e1%85%a6\/","title":{"rendered":"Pandas: \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \uc18c\uacc4\ub97c \ucd94\uac00\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Pandas \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \ubd80\ubd84\ud569\uc744 \ucd94\uac00\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788\ub3c4 pandas\uc758 \ub0b4\uc7a5 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uba74 \uc27d\uac8c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608: Pandas PivotTable\uc5d0 \uc18c\uacc4 \ucd94\uac00<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 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;\">#createDataFrame\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;\">position<\/span> ': ['G', 'G', 'F', 'F', 'G', 'F', 'F', 'F'],\n                   ' <span style=\"color: #ff0000;\">all_star<\/span> ': ['Y', 'N', 'Y', 'Y', 'N', 'N', 'N', 'Y'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [4, 4, 6, 8, 9, 5, 5, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team position all_star points\n0 AGY 4\n1 AGN 4\n2 AFY 6\n3 AFY 8\n4 BGN 9\n5 BFN 5\n6 BFN 5\n7 BFY 12<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 <strong>team<\/strong> , <strong>all_star<\/strong> \ubc0f <strong>position<\/strong> \uc758 \uac01 \uc870\ud569\uc5d0 \ub300\ud55c <strong>\ud3ec\uc778\ud2b8<\/strong> \ud569\uacc4\ub97c \ud45c\uc2dc\ud558\ub294 pandas\uc758 \ud53c\ubc97 \ud14c\uc774\ube14\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create pivot table\n<span style=\"color: #000000;\">my_table = pd. <span style=\"color: #3366ff;\">pivot_table<\/span> (df, values=' <span style=\"color: #ff0000;\">points<\/span> ',\n                              index=[' <span style=\"color: #ff0000;\">team<\/span> ', ' <span style=\"color: #ff0000;\">all_star<\/span> '],\n                              columns=' <span style=\"color: #ff0000;\">position<\/span> ',\n                              aggfunc=' <span style=\"color: #ff0000;\">sum<\/span> ')\n\n<span style=\"color: #008080;\">#view pivot table\n<\/span><span style=\"color: #008000;\">print<\/span> (my_table)\n\nFG position\nteam all_star           \nAN NaN 4.0\n     Y 14.0 4.0\nBN 10.0 9.0\n     Y 12.0 NaN<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c \uac01 \ud300\uacfc \uc704\uce58\uc5d0 \ub300\ud55c \uc18c\uacc4 \uc810\uc218\ub97c \ud45c\uc2dc\ud558\ub294 <strong>\uc18c\uacc4<\/strong> \ud589\uc744 \ucd94\uac00\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \uc704\ud574 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#add subtotals row to pivot table\n<\/span>p.d. <span style=\"color: #3366ff;\">concat<\/span> ([\n    y. <span style=\"color: #3366ff;\">append<\/span> ( <span style=\"color: #3366ff;\">y.sum<\/span> (). <span style=\"color: #3366ff;\">rename<\/span> ((x, ' <span style=\"color: #ff0000;\">Total<\/span> ')))\n    <span style=\"color: #008000;\">for<\/span> x, y <span style=\"color: #008000;\">in<\/span> my_table. <span style=\"color: #3366ff;\">groupby<\/span> (level= <span style=\"color: #008000;\">0<\/span> )\n]). <span style=\"color: #3366ff;\">append<\/span> ( <span style=\"color: #3366ff;\">my_table.sum<\/span> (). <span style=\"color: #3366ff;\">rename<\/span> ((' <span style=\"color: #ff0000;\">Large<\/span> ', ' <span style=\"color: #ff0000;\">Total<\/span> ')))\n\n\tposition F G\nteam all_star\t\t\nA N NaN 4.0\n               Y 7.0 4.0\n           Overall 7.0 8.0\nB N 5.0 9.0\n               Y 12.0 NaN\n           Total 17.0 9.0\nGrand Total 24.0 17.0\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c \uac01 \ud300\uacfc \uc9c1\uc704\uc5d0 \ub300\ud55c \uc18c\uacc4 \uc810\uc218\ub97c \ud45c\uc2dc\ud558\ub294 \ub450 \uac1c\uc758 \uc18c\uacc4 \ud589\uacfc \uac01 \uc5f4\uc758 \ucd1d\ud569\uacc4\ub97c \ud45c\uc2dc\ud558\ub294 \ucd1d\ud569\uacc4 \ud589\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.pivot_table.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> <strong>pandasivot_table()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\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-\u1111\u1175\u1107\u1165\u11ba-\u1110\u1166\u110b\u1175\u1107\u1173\u11af-\u1109\u116e\/\" target=\"_blank\" rel=\"noopener\">Pandas: \uac12 \uac1c\uc218\uac00 \ud3ec\ud568\ub41c \ud53c\ubc97 \ud14c\uc774\ube14\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1111\u1175\u1107\u1165\u11ba-\u1110\u1166\u110b\u1175\u1107\u1173\u11af\u110b\u1173\u11ab-nan\u110b\u1173\u11af-0\u110b\u1173\u1105\u1169-\u1107\u1161\u1101\u116e\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas: \ud53c\ubc97 \ud14c\uc774\ube14\uc758 NaN \uac12\uc744 0\uc73c\ub85c \ubc14\uafb8\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1111\u1175\u1107\u1165\u11ba-\u1110\u1166\u110b\u1175\u1107\u1173\u11af\u110b\u1173\u11af-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111\u1173\u1105\u1166\u110b\u1175\u11b7\u110b\u1173\u1105\u1169\/\" target=\"_blank\" rel=\"noopener\">Pandas: \ud53c\ubc97 \ud14c\uc774\ube14\uc744 DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pandas \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \ubd80\ubd84\ud569\uc744 \ucd94\uac00\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ud589\ud788\ub3c4 pandas\uc758 \ub0b4\uc7a5 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uba74 \uc27d\uac8c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608: Pandas PivotTable\uc5d0 \uc18c\uacc4 \ucd94\uac00 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4. import pandas as pd #createDataFrame df = pd. DataFrame ({&#8216; team &#8216;: [&#8216;A&#8217;, &#8216;A&#8217;, &#8216;A&#8217;, [&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-3274","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: \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \uc18c\uacc4\ub97c \ucd94\uac00\ud558\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \uc18c\uacc4\ub97c \ucd94\uac00\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc2dc\uc640 \ud568\uaed8 \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\/\u1112\u1161\u11b8\u1100\u1168-\u110b\u1161\u1105\u1162-\u1111\u1162\u11ab\u1103\u1165-\u1111\u1175\u1107\u1165\u11ba-\u1110\u1166\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: \ud53c\ubc97 \ud14c\uc774\ube14\uc5d0 \uc18c\uacc4\ub97c \ucd94\uac00\ud558\ub294 \ubc29\ubc95 - 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