{"id":2824,"date":"2023-07-20T12:48:52","date_gmt":"2023-07-20T12:48:52","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%be%d0%bf%d0%b5%d1%80%d0%b0%d1%82%d0%be%d1%80-%d1%81%d0%bb%d1%83%d1%87%d0%b0%d1%8f-%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b\/"},"modified":"2023-07-20T12:48:52","modified_gmt":"2023-07-20T12:48:52","slug":"%d0%be%d0%bf%d0%b5%d1%80%d0%b0%d1%82%d0%be%d1%80-%d1%81%d0%bb%d1%83%d1%87%d0%b0%d1%8f-%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%be%d0%bf%d0%b5%d1%80%d0%b0%d1%82%d0%be%d1%80-%d1%81%d0%bb%d1%83%d1%87%d0%b0%d1%8f-%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b\/","title":{"rendered":"\u041a\u0430\u043a \u043d\u0430\u043f\u0438\u0441\u0430\u0442\u044c \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 case \u0432 pandas (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u041e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 Case<\/strong> \u2014 \u044d\u0442\u043e \u0442\u0438\u043f \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0446\u0438\u043a\u043b\u0438\u0447\u0435\u0441\u043a\u0438 \u043f\u0435\u0440\u0435\u0431\u0438\u0440\u0430\u0435\u0442 \u0443\u0441\u043b\u043e\u0432\u0438\u044f \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u043f\u0435\u0440\u0432\u043e\u0433\u043e \u0443\u0441\u043b\u043e\u0432\u0438\u044f.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0421\u0430\u043c\u044b\u0439 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0441\u043f\u043e\u0441\u043e\u0431 \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 case \u0432 DataFrame Pandas \u2014 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e <strong>NumPywhere()<\/strong> , \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441:<\/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;\">\u042d\u0442\u0430 \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u0430\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u044f \u043f\u0440\u043e\u0441\u043c\u0430\u0442\u0440\u0438\u0432\u0430\u0435\u0442 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 \u0441 \u0438\u043c\u0435\u043d\u0435\u043c <strong>col2<\/strong> \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u04351<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 2 \u043c\u0435\u043d\u044c\u0448\u0435 9<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u04352<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 2 \u043c\u0435\u043d\u044c\u0448\u0435 12.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>value3<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 2 \u043c\u0435\u043d\u044c\u0448\u0435 15.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>value4<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u043d\u0438 \u043e\u0434\u043d\u043e \u0438\u0437 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u0443\u0441\u043b\u043e\u0432\u0438\u0439 \u043d\u0435 \u0432\u0435\u0440\u043d\u043e.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u0443 \u0444\u0443\u043d\u043a\u0446\u0438\u044e \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\u041f\u0440\u0438\u043c\u0435\u0440: \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 \u0441\u043b\u0443\u0447\u0430\u044f \u0432 Pandas<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas:<\/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;\">\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u043d\u0430\u043f\u0438\u0441\u0430\u043d\u0438\u044f \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440\u0430 case, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0441\u043e\u0437\u0434\u0430\u0435\u0442 \u043d\u043e\u0432\u044b\u0439 \u0441\u0442\u043e\u043b\u0431\u0435\u0446 \u0441 \u0438\u043c\u0435\u043d\u0435\u043c <strong>class<\/strong> , \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u044f\u044e\u0442\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f\u043c\u0438 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 <strong>\u0442\u043e\u0447\u0435\u043a<\/strong> :<\/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;\">\u041e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 case \u043f\u0440\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u043b \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 <strong>\u0442\u043e\u0447\u0435\u043a<\/strong> \u0438 \u0432\u0435\u0440\u043d\u0443\u043b:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u041f\u043b\u043e\u0445\u043e<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 \u00ab\u0431\u0430\u043b\u043b\u044b\u00bb \u0431\u044b\u043b\u043e \u043c\u0435\u043d\u044c\u0448\u0435 9.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u041e\u041a<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 \u0431\u0430\u043b\u043b\u043e\u0432 \u0431\u044b\u043b\u043e \u043c\u0435\u043d\u044c\u0448\u0435 12.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u0425\u043e\u0440\u043e\u0448\u043e<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 \u00ab\u0431\u0430\u043b\u043b\u044b\u00bb \u0431\u044b\u043b\u043e \u043c\u0435\u043d\u044c\u0448\u0435 15.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u00ab <strong>\u041e\u0442\u043b\u0438\u0447\u043d\u043e<\/strong> \u00bb, \u0435\u0441\u043b\u0438 \u043d\u0438 \u043e\u0434\u043d\u043e \u0438\u0437 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u0443\u0441\u043b\u043e\u0432\u0438\u0439 \u043d\u0435 \u0432\u0435\u0440\u043d\u043e.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435<\/strong> . \u041f\u043e\u043b\u043d\u0443\u044e \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044e \u043f\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 <strong>NumPywhere()<\/strong> \u043c\u043e\u0436\u043d\u043e \u043d\u0430\u0439\u0442\u0438 <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.where.html\" target=\"_blank\" rel=\"noopener\">\u0437\u0434\u0435\u0441\u044c<\/a> .<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u0434\u0440\u0443\u0433\u0438\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438 \u0432 Pandas:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u043e\u0437\u0434\u0430\u0432\u0430\u0442\u044c-\u043f\u0430\u043d\u0434\u044b-\u043d\u0430-\u043e\u0441\u043d\u043e\u0432\u0435-\u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u043d\u043e\u0432\u044b\u0439 \u0441\u0442\u043e\u043b\u0431\u0435\u0446 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u0443\u0441\u043b\u043e\u0432\u0438\u044f \u0432 Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0447\u0438\u0441\u043b\u043e-\u0438\u043b\u0438-\u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e-\u0443\u0441\u043b\u043e\u0432\u0438\u0438\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e NumPy Where() \u0441 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c\u0438 \u0443\u0441\u043b\u043e\u0432\u0438\u044f\u043c\u0438<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u041e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 Case \u2014 \u044d\u0442\u043e \u0442\u0438\u043f \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0446\u0438\u043a\u043b\u0438\u0447\u0435\u0441\u043a\u0438 \u043f\u0435\u0440\u0435\u0431\u0438\u0440\u0430\u0435\u0442 \u0443\u0441\u043b\u043e\u0432\u0438\u044f \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0438 \u043f\u0435\u0440\u0432\u043e\u0433\u043e \u0443\u0441\u043b\u043e\u0432\u0438\u044f. \u0421\u0430\u043c\u044b\u0439 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u0441\u043f\u043e\u0441\u043e\u0431 \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440 case \u0432 DataFrame Pandas \u2014 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e NumPywhere() , \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441: 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; [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2824","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u041a\u0430\u043a \u043d\u0430\u043f\u0438\u0441\u0430\u0442\u044c \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u0434\u0435\u043b\u0430 \u0432 Pandas (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c) - Statorials<\/title>\n<meta name=\"description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u043d\u0430\u043f\u0438\u0441\u0430\u0442\u044c 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