{"id":3697,"date":"2023-07-16T01:46:50","date_gmt":"2023-07-16T01:46:50","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%80%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6-%e1%84%84%e1%85%a1%e1%84%85%e1%85%a1-%e1%84%87%e1%85%ae\/"},"modified":"2023-07-16T01:46:50","modified_gmt":"2023-07-16T01:46:50","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%80%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6-%e1%84%84%e1%85%a1%e1%84%85%e1%85%a1-%e1%84%87%e1%85%ae","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%80%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6-%e1%84%84%e1%85%a1%e1%84%85%e1%85%a1-%e1%84%87%e1%85%ae\/","title":{"rendered":"Pandas: \uc870\uac74\uc5d0 \ub530\ub77c \ubd80\uc6b8 \uc5f4\uc744 \ub9cc\ub4dc\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\uc5d0\uc11c \uc870\uac74 \uae30\ubc18 \ubd80\uc6b8 \uc5f4\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">boolean_column<\/span> '] = np. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">some_column<\/span> '] &gt; 15, <span style=\"color: #008000;\">True<\/span> , <span style=\"color: #008000;\">False<\/span> )\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \ud2b9\uc815 \uad6c\ubb38\uc740 \ub450 \uac00\uc9c0 \uac00\ub2a5\ud55c \uac12\uc774 \uc788\ub294 \uc0c8 \ubd80\uc6b8 \uc5f4\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>some_column<\/strong> \uc758 \uac12\uc774 15\ubcf4\ub2e4 \ud06c\uba74 <strong>\ucc38\uc785\ub2c8\ub2e4<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>some_column<\/strong> \uc758 \uac12\uc774 15\ubcf4\ub2e4 \uc791\uac70\ub098 \uac19\uc73c\uba74 <strong>False\uc785\ub2c8\ub2e4<\/strong> .<\/span><\/li>\n<\/ul>\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<h2> <span style=\"color: #000000;\"><strong>\uc608: Pandas\uc758 \uc870\uac74\uc744 \uae30\ubc18\uc73c\ub85c \ubd80\uc6b8 \uc5f4 \uc0dd\uc131<\/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<span style=\"color: #000000;\">\ndf = 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;\">points<\/span> ': [5, 17, 7, 19, 12, 13, 9, 24]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points\n0 to 5\n1 to 17\n2 to 7\n3 to 19\n4 B 12\n5 B 13\n6 B 9\n7 B 24   \n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud3ec\uc778\ud2b8 \uc5f4\uc758 \uac12\uc774 15\ubcf4\ub2e4 \ud06c\uba74 <strong>True\ub97c<\/strong> \ubc18\ud658\ud558\uace0 \uadf8\ub807\uc9c0 \uc54a\uc73c\uba74 <strong>False\ub97c<\/strong> \ubc18\ud658\ud558\ub294 <strong>good_player<\/strong> \ub77c\ub294 \uc0c8 \uc5f4\uc744 \ub9cc\ub4e4 \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: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#create new boolean column based on value in points column\n<\/span>df[' <span style=\"color: #ff0000;\">good_player<\/span> '] = np. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">points<\/span> '] &gt; 15, <span style=\"color: #008000;\">True<\/span> , <span style=\"color: #008000;\">False<\/span> )\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points good_player\n0 To 5 False\n1 To 17 True\n2 To 7 False\n3 To 19 True\n4 B 12 False\n5 B 13 False\n6 B 9 False\n7 B 24 True<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>good_player<\/strong> \ub77c\ub294 \uc0c8 \uc5f4\uc5d0\ub294 <strong>True<\/strong> \ub610\ub294 <strong>False<\/strong> \ub77c\ub294 \ub450 \uac00\uc9c0 \uac12\ub9cc \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>dtypes()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc0c8\ub85c\uc6b4 <strong>good_player<\/strong> \uc5f4\uc774 \uc2e4\uc81c\ub85c \ubd80\uc6b8 \uc5f4\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;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\"><span style=\"color: #008080;\">#display data type of good_player column<\/span>\n<\/span>df[' <span style=\"color: #ff0000;\">good_player<\/span> ']. <span style=\"color: #3366ff;\">dtype\n\n<\/span>dtype('bool')\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc0c8\ub85c\uc6b4 <strong>good_player<\/strong> \uc5f4\uc740 \uc2e4\uc81c\ub85c \ubd80\uc6b8 \uc5f4\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub610\ud55c \uc6d0\ud558\ub294 \uacbd\uc6b0 <strong>True<\/strong> \ubc0f <strong>False<\/strong> \ub300\uc2e0 <strong>1<\/strong> \ubc0f <strong>0<\/strong> \uacfc \uac19\uc740 \uc22b\uc790 \uac12\uc744 \ubc18\ud658\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: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#create new boolean column based on value in points column\n<\/span>df[' <span style=\"color: #ff0000;\">good_player<\/span> '] = np. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">points<\/span> '] &gt; 15, <span style=\"color: #008000;\">1<\/span> ,<\/span> <span style=\"color: #000000;\"><span style=\"color: #008000;\">0<\/span> <span style=\"color: #000000;\">)\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span><\/span><span style=\"color: #008000;\">print<\/span> <span style=\"color: #000000;\">(df)\n\n  team points good_player\n0 to 5 0\n1 To 17 1\n2 to 7 0\n3 A 19 1\n4 B 12 0\n5 B 13 0\n6 B 9 0\n7 B 24 1\n<\/span><\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c <strong>\ud3ec\uc778\ud2b8<\/strong> \uc5f4\uc758 \ud574\ub2f9 \uac12\uc774 15\ubcf4\ub2e4 \ud06c\uba74 <strong>good_player<\/strong> \uc5f4\uc5d0 <strong>1<\/strong> \uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub807\uc9c0 \uc54a\uc73c\uba74 \uac12 <strong>0<\/strong> \uc774 \ud3ec\ud568\ub429\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\/pandas-loc-\u110b\u1167\u1105\u1165-\u110c\u1169\u1100\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \uc5ec\ub7ec \uc870\uac74\uc744 \uae30\ubc18\uc73c\ub85c \ud589\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u110b\u1167\u11af\u110b\u1173\u11af-\u1100\u1175\u1107\u1161\u11ab\u110b\u1173\u1105\u1169-\u1111\u1162\u11ab\u1103\u1165-\u1106\u1161\u11ab\u1103\u1173\u11af\u1100\u1175\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc758 \uc870\uac74\uc744 \uae30\ubc18\uc73c\ub85c \uc0c8 \uc5f4\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u110b\u1167\u1105\u1165-\u110c\u1169\u1100\u1165\u11ab\u110b\u1173\u11af-\u1111\u1175\u11af\u1110\u1165\u1105\u1175\u11bc\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\uc5ec\ub7ec \uc870\uac74\uc5d0\uc11c Pandas DataFrame\uc744 \ud544\ud130\ub9c1\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\uc5d0\uc11c \uc870\uac74 \uae30\ubc18 \ubd80\uc6b8 \uc5f4\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df[&#8216; boolean_column &#8216;] = np. where (df[&#8216; some_column &#8216;] &gt; 15, True , False ) \uc774 \ud2b9\uc815 \uad6c\ubb38\uc740 \ub450 \uac00\uc9c0 \uac00\ub2a5\ud55c \uac12\uc774 \uc788\ub294 \uc0c8 \ubd80\uc6b8 \uc5f4\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4. some_column \uc758 \uac12\uc774 15\ubcf4\ub2e4 \ud06c\uba74 \ucc38\uc785\ub2c8\ub2e4 . some_column \uc758 \uac12\uc774 15\ubcf4\ub2e4 \uc791\uac70\ub098 \uac19\uc73c\uba74 False\uc785\ub2c8\ub2e4 . [&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-3697","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: \uc870\uac74\uc5d0 \ub530\ub77c \ubd80\uc6b8 \uc5f4\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas DataFrame\uc758 \uc870\uac74\uc744 \uae30\ubc18\uc73c\ub85c \ubd80\uc6b8 \uc5f4\uc744 \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\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 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