{"id":2824,"date":"2023-07-20T12:48:52","date_gmt":"2023-07-20T12:48:52","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%89%e1%85%a1%e1%84%85%e1%85%a8-%e1%84%8c%e1%85%b5%e1%86%ab%e1%84%89%e1%85%ae%e1%86%af\/"},"modified":"2023-07-20T12:48:52","modified_gmt":"2023-07-20T12:48:52","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%89%e1%85%a1%e1%84%85%e1%85%a8-%e1%84%8c%e1%85%b5%e1%86%ab%e1%84%89%e1%85%ae%e1%86%af","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%89%e1%85%a1%e1%84%85%e1%85%a8-%e1%84%8c%e1%85%b5%e1%86%ab%e1%84%89%e1%85%ae%e1%86%af\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc0ac\ub840 \uc124\uba85\uc744 \uc791\uc131\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>Case \ubb38\uc740<\/strong> \uc870\uac74\uc744 \uc21c\ud658\ud558\uace0 \uccab \ubc88\uc9f8 \uc870\uac74\uc774 \ucda9\uc871\ub418\uba74 \uac12\uc744 \ubc18\ud658\ud558\ub294 \ubb38 \uc720\ud615\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Pandas DataFrame\uc5d0\uc11c Case \ubb38\uc744 \uad6c\ud604\ud558\ub294 \uac00\uc7a5 \uac04\ub2e8\ud55c \ubc29\ubc95\uc740 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 <strong>NumPywhere()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">new_column<\/span> '] = np. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">col2<\/span> ']&lt;9, 'value1',\n                   n.p. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">col2<\/span> ']&lt;12, 'value2',\n                   n.p. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">col2<\/span> ']&lt;15, 'value3', 'value4')))\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \ud2b9\uc815 \ud568\uc218\ub294 <strong>col2<\/strong> \ub77c\ub294 \uc5f4\uc758 \uac12\uc744 \ubcf4\uace0 \ub2e4\uc74c\uc744 \ubc18\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">col2\uc758 \uac12\uc774 9\ubcf4\ub2e4 \uc791\uc740 \uacbd\uc6b0 \u201c <strong>value1<\/strong> \u201d<\/span><\/li>\n<li> <span style=\"color: #000000;\">col2\uc758 \uac12\uc774 12\ubcf4\ub2e4 \uc791\uc740 \uacbd\uc6b0 \u201c <strong>value2<\/strong> \u201d<\/span><\/li>\n<li> <span style=\"color: #000000;\">col2\uc758 \uac12\uc774 15\ubcf4\ub2e4 \uc791\uc740 \uacbd\uc6b0 &#8221; <strong>value3<\/strong> &#8220;<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc774\uc804 \uc870\uac74 \uc911 \uc5b4\ub290 \uac83\ub3c4 true\uac00 \uc544\ub2cc \uacbd\uc6b0 &#8221; <strong>value4<\/strong> &#8220;<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\uc608: Pandas\uc758 \uc0ac\ub840 \ubb38<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 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<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">player<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [6, 8, 9, 9, 12, 14, 15, 17, 19, 22]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tplayer points\n0 1 6\n1 2 8\n2 3 9\n3 4 9\n4 5 12\n5 6 14\n6 7 15\n7 8 17\n8 9 19\n9 10 22\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec <strong>\ud3ec\uc778\ud2b8<\/strong> \uc5f4\uc758 \uac12\uc5d0 \ub530\ub77c \uac12\uc774 \uacb0\uc815\ub418\ub294 <strong>class<\/strong> \ub77c\ub294 \uc0c8 \uc5f4\uc744 \uc0dd\uc131\ud558\ub294 Case \ubb38\uc744 \uc791\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#add 'class' column using case-statement logic\n<\/span>df[' <span style=\"color: #ff0000;\">class<\/span> '] = np. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">points<\/span> ']&lt;9, 'Bad',\n              n.p. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">points<\/span> ']&lt;12, 'OK',\n              n.p. <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">points<\/span> ']&lt;15, 'Good', 'Great')))\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span>df\n\n\tplayer points class\n0 1 6 Bad\n1 2 8 Bad\n2 3 9 OK\n3 4 9 OK\n4 5 12 Good\n5 6 14 Good\n6 7 15 Great\n7 8 17 Great\n8 9 19 Great\n9 10 22 Great\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Case \ubb38\uc740 <strong>\ud3ec\uc778\ud2b8<\/strong> \uc5f4\uc758 \uac12\uc744 \ubcf4\uace0 \ub2e4\uc74c\uc744 \ubc18\ud658\ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\ud3ec\uc778\ud2b8 \uc5f4\uc758 \uac12\uc774 9 \ubbf8\ub9cc\uc778 \uacbd\uc6b0 &#8221; <strong>\ub098\uc068<\/strong> &#8220;<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud3ec\uc778\ud2b8 \uc5f4\uc758 \uac12\uc774 12 \ubbf8\ub9cc\uc778 \uacbd\uc6b0 &#8221; <strong>OK<\/strong> &#8220;<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud3ec\uc778\ud2b8 \uc5f4\uc758 \uac12\uc774 15 \ubbf8\ub9cc\uc778 \uacbd\uc6b0 &#8221; <strong>\uc88b\uc74c<\/strong> &#8220;<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc774\uc804 \uc870\uac74 \uc911 \uc5b4\ub290 \uac83\ub3c4 \ucc38\uc774 \uc544\ub2cc \uacbd\uc6b0 \u201c <strong>\uc88b\uc74c<\/strong> \u201d<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : <strong>NumPywhere()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub294 <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.where.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> \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 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\/\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\/numpy-\u1104\u1169\u1102\u1173\u11ab-\u110b\u1167\u1105\u1165-\u110c\u1169\u1100\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">\uc5ec\ub7ec \uc870\uac74\uc73c\ub85c NumPy Where() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Case \ubb38\uc740 \uc870\uac74\uc744 \uc21c\ud658\ud558\uace0 \uccab \ubc88\uc9f8 \uc870\uac74\uc774 \ucda9\uc871\ub418\uba74 \uac12\uc744 \ubc18\ud658\ud558\ub294 \ubb38 \uc720\ud615\uc785\ub2c8\ub2e4. Pandas DataFrame\uc5d0\uc11c Case \ubb38\uc744 \uad6c\ud604\ud558\ub294 \uac00\uc7a5 \uac04\ub2e8\ud55c \ubc29\ubc95\uc740 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 NumPywhere() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. df[&#8216; new_column &#8216;] = np. where (df[&#8216; col2 &#8216;]&lt;9, &#8216;value1&#8217;, n.p. where (df[&#8216; col2 &#8216;]&lt;12, &#8216;value2&#8217;, n.p. where (df[&#8216; col2 &#8216;]&lt;15, &#8216;value3&#8217;, &#8216;value4&#8217;))) \uc774 \ud2b9\uc815 \ud568\uc218\ub294 col2 [&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-2824","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 \uc0ac\ub840 \uc124\uba85\uc744 \uc791\uc131\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - 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