{"id":2092,"date":"2023-07-23T17:39:42","date_gmt":"2023-07-23T17:39:42","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d0%bf%d0%be%d0%b4%d0%b0%d1%82%d1%8c-%d0%b7%d0%b0%d1%8f%d0%b2%d0%ba%d1%83-%d0%bd%d0%b0-%d1%81%d0%b0%d0%b8%d1%82%d0%b5\/"},"modified":"2023-07-23T17:39:42","modified_gmt":"2023-07-23T17:39:42","slug":"%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d0%bf%d0%be%d0%b4%d0%b0%d1%82%d1%8c-%d0%b7%d0%b0%d1%8f%d0%b2%d0%ba%d1%83-%d0%bd%d0%b0-%d1%81%d0%b0%d0%b8%d1%82%d0%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d0%bf%d0%be%d0%b4%d0%b0%d1%82%d1%8c-%d0%b7%d0%b0%d1%8f%d0%b2%d0%ba%d1%83-%d0%bd%d0%b0-%d1%81%d0%b0%d0%b8%d1%82%d0%b5\/","title":{"rendered":"\u041a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c pandas apply() \u043d\u0430 \u043c\u0435\u0441\u0442\u0435"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0424\u0443\u043d\u043a\u0446\u0438\u044e pandas <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.apply.html\" target=\"_blank\" rel=\"noopener\">apply()<\/a> \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u043b\u044f \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043a \u0441\u0442\u0440\u043e\u043a\u0430\u043c \u0438\u043b\u0438 \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c Pandas DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u042d\u0442\u0430 \u0444\u0443\u043d\u043a\u0446\u0438\u044f \u043e\u0442\u043b\u0438\u0447\u0430\u0435\u0442\u0441\u044f \u043e\u0442 \u0434\u0440\u0443\u0433\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439, \u0442\u0430\u043a\u0438\u0445 \u043a\u0430\u043a <strong>drop()<\/strong> \u0438 <strong>replace()<\/strong> , \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0442 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442 inplace:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">drop<\/span> ([' <span style=\"color: #ff0000;\">column1<\/span> '], inplace= <span style=\"color: #008000;\">True<\/span> )\n\ndf. <span style=\"color: #3366ff;\">rename<\/span> ({' <span style=\"color: #ff0000;\">old_column<\/span> ': ' <span style=\"color: #ff0000;\">new_column<\/span> '}, inplace= <span style=\"color: #008000;\">True<\/span> )\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0424\u0443\u043d\u043a\u0446\u0438\u044f <strong>apply()<\/strong> \u043d\u0435 \u0438\u043c\u0435\u0435\u0442 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u0430 inplace, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u0434\u043b\u044f \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0440\u0430\u0437\u043c\u0435\u0449\u0435\u043d\u043d\u043e\u0433\u043e DataFrame \u043c\u044b \u0434\u043e\u043b\u0436\u043d\u044b \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:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df = df. <span style=\"color: #3366ff;\">apply<\/span> ( <span style=\"color: #008000;\">lambda<\/span> x: x* <span style=\"color: #008000;\">2<\/span> )<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u0445 \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\u043e\u0442 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 \u0441\u043e \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c 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\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 1. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0430 apply() \u0432\u043c\u0435\u0441\u0442\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0430<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u0434\u0435\u043c\u043e\u043d\u0441\u0442\u0440\u0438\u0440\u0443\u0435\u0442, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c <strong>apply()<\/strong> \u0434\u043b\u044f \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u0444\u0440\u0435\u0439\u043c\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043d\u0430 \u043c\u0435\u0441\u0442\u0435:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#multiply all values in 'points' column by 2 in place\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">points<\/span> '] = df. <span style=\"color: #3366ff;\">points<\/span> . <span style=\"color: #3366ff;\">apply<\/span> ( <span style=\"color: #008000;\">lambda<\/span> x: x* <span style=\"color: #008000;\">2<\/span> )\n\n<span style=\"color: #008080;\">#view updated DataFrame<\/span>\ndf\n\npoints assists rebounds\n0 50 5 11\n1 24 7 8\n2 30 7 10\n3 28 9 6\n4 38 12 6\n5 46 9 5\n6 50 9 9\n7 58 4 12\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 2. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0439\u0442\u0435 \u043c\u0435\u0442\u043e\u0434 apply() \u0434\u043b\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432.<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u0434\u0435\u043c\u043e\u043d\u0441\u0442\u0440\u0438\u0440\u0443\u0435\u0442, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c <strong>apply()<\/strong> \u0434\u043b\u044f \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0444\u0440\u0435\u0439\u043c\u0430 \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">multiply all values in 'points' and 'rebounds' column by 2 in place<\/span>\ndf[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']] = df[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">apply<\/span> ( <span style=\"color: #008000;\">lambda<\/span> x: x* <span style=\"color: #008000;\">2<\/span> )\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span>df\n\n\tpoints assists rebounds\n0 50 5 22\n1 24 7 16\n2 30 7 20\n3 28 9 12\n4 38 12 12\n5 46 9 10\n6 50 9 18\n7 58 4 24\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 3. \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0439\u0442\u0435 apply() \u0434\u043b\u044f \u0432\u0441\u0435\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432.<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c <strong>apply()<\/strong> \u0434\u043b\u044f \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0432\u0441\u0435\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432\u043e \u0444\u0440\u0435\u0439\u043c\u0435 \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#multiply values in all columns by 2\n<\/span>df = df. <span style=\"color: #3366ff;\">apply<\/span> ( <span style=\"color: #008000;\">lambda<\/span> x: x* <span style=\"color: #008000;\">2<\/span> )\n\n<span style=\"color: #008080;\">#view updated DataFrame<\/span>\ndf\n\n\tpoints assists rebounds\n0 50 10 22\n1 24 14 16\n2 30 14 20\n3 28 18 12\n4 38 24 12\n5 46 18 10\n6 50 18 18\n7 58 8 24\n<\/strong><\/pre>\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 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u0432 pandas:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u044d\u0442\u043e-\u0441\u0442\u043e\u043b\u0431\u0446\u044b-\u043f\u0430\u043d\u0434\u044b\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u043f\u043e\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u0443\u043c\u043c\u0443 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u0440\u0435\u0434\u043d\u0438\u0438-\u0441\u0442\u043e\u043b\u0431\u0435\u0446-\u043f\u0430\u043d\u0434\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 Pandas<\/a><br \/> \u041a\u0430\u043a \u043d\u0430\u0439\u0442\u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 Pandas<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0424\u0443\u043d\u043a\u0446\u0438\u044e pandas apply() \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u043b\u044f \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043a \u0441\u0442\u0440\u043e\u043a\u0430\u043c \u0438\u043b\u0438 \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c Pandas DataFrame. \u042d\u0442\u0430 \u0444\u0443\u043d\u043a\u0446\u0438\u044f \u043e\u0442\u043b\u0438\u0447\u0430\u0435\u0442\u0441\u044f \u043e\u0442 \u0434\u0440\u0443\u0433\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439, \u0442\u0430\u043a\u0438\u0445 \u043a\u0430\u043a drop() \u0438 replace() , \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0442 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442 inplace: df. drop ([&#8216; column1 &#8216;], inplace= True ) df. rename ({&#8216; old_column &#8216;: &#8216; new_column &#8216;}, inplace= True ) \u0424\u0443\u043d\u043a\u0446\u0438\u044f apply() \u043d\u0435 \u0438\u043c\u0435\u0435\u0442 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u0430 inplace, [&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-2092","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 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c Pandas apply() \u043d\u0430 \u043c\u0435\u0441\u0442\u0435 \u2013 \u0421\u0442\u0430\u0442\u043e\u0440\u0438\u0430\u043b\u044b<\/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 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e pandas apply(), \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u0432.\" \/>\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\/ru\/\u043f\u0430\u043d\u0434\u044b-\u043f\u043e\u0434\u0430\u0442\u044c-\u0437\u0430\u044f\u0432\u043a\u0443-\u043d\u0430-\u0441\u0430\u0438\u0442\u0435\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c Pandas apply() \u043d\u0430 \u043c\u0435\u0441\u0442\u0435 \u2013 \u0421\u0442\u0430\u0442\u043e\u0440\u0438\u0430\u043b\u044b\" \/>\n<meta property=\"og:description\" content=\"\u0412 \u044d\u0442\u043e\u043c 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