{"id":955,"date":"2023-07-28T04:39:16","date_gmt":"2023-07-28T04:39:16","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%bc%d0%b0%d0%ba%d1%81%d0%b8%d0%bc%d0%b0%d0%bb%d1%8c%d0%bd%d0%be%d0%b5-%d0%b7%d0%bd%d0%b0%d1%87%d0%b5%d0%bd%d0%b8%d0%b5-%d0%bd%d0%b0-%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d1%83-r\/"},"modified":"2023-07-28T04:39:16","modified_gmt":"2023-07-28T04:39:16","slug":"%d0%bc%d0%b0%d0%ba%d1%81%d0%b8%d0%bc%d0%b0%d0%bb%d1%8c%d0%bd%d0%be%d0%b5-%d0%b7%d0%bd%d0%b0%d1%87%d0%b5%d0%bd%d0%b8%d0%b5-%d0%bd%d0%b0-%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d1%83-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%bc%d0%b0%d0%ba%d1%81%d0%b8%d0%bc%d0%b0%d0%bb%d1%8c%d0%bd%d0%be%d0%b5-%d0%b7%d0%bd%d0%b0%d1%87%d0%b5%d0%bd%d0%b8%d0%b5-%d0%bd%d0%b0-%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d1%83-r\/","title":{"rendered":"\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 \u0434\u043b\u044f \u0433\u0440\u0443\u043f\u043f\u044b \u0432 r"},"content":{"rendered":"

<\/p>\n

\n

\u0427\u0430\u0441\u0442\u043e \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \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 \u043a\u0430\u0436\u0434\u043e\u0439 \u0433\u0440\u0443\u043f\u043f\u044b \u0432\u043e \u0444\u0440\u0435\u0439\u043c\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 R. \u041a \u0441\u0447\u0430\u0441\u0442\u044c\u044e, \u044d\u0442\u043e \u043b\u0435\u0433\u043a\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043f\u0430\u043a\u0435\u0442\u0430 dplyr<\/a> .<\/span><\/p>\n

\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 \u044d\u0442\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/p>\n

 #create data frame<\/span>\ndf <- data.frame(team = c('A', 'A', 'A', 'B', 'B', 'B', 'B'),\n                 position = c('G', 'F', 'F', 'G', 'G', 'G', 'F'),\n                 points = c(12, 15, 19, 22, 34, 34, 39))\n\n#view data frame\n<\/span>df\n\n  team position points\n1 AG 12\n2 AF15\n3 FY 19\n4 BG 22\n5 BG 34\n6 BG 34\n7 BF 39\n<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043c\u0435\u0440 1. \u041d\u0430\u0439\u0434\u0438\u0442\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0433\u0440\u0443\u043f\u043f\u044b.<\/strong><\/span><\/h3>\n
 \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 \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 \u0434\u043b\u044f \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u044e:<\/span><\/p>\n
 library(dplyr)<\/span>\n\n#find max value by team and position<\/span>\ndf %>%\n  group_by<\/span> (team, position) %>%\n  summarize<\/span> (max = max(points, na.rm= TRUE<\/span> ))\n\n# A tibble: 4 x 3\n# Groups: team [?]\n  team position max\n      \n1AF 19.0\n2 AG 12.0\n3 BF 39.0\n4 BG 34.0<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043c\u0435\u0440 2. \u0412\u043e\u0437\u0432\u0440\u0430\u0442 \u0441\u0442\u0440\u043e\u043a, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0438\u0445 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u0433\u0440\u0443\u043f\u043f\u044b.<\/strong><\/span><\/h3>\n
 \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 \u0432\u0435\u0440\u043d\u0443\u0442\u044c \u0441\u0442\u0440\u043e\u043a\u0438, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0438\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0438 \u043f\u043e\u0437\u0438\u0446\u0438\u0438:<\/span><\/p>\n
 library(dplyr)<\/span>\n\n#find rows that contain max points by team and position<\/span>\ndf %>%\n  group_by<\/span> (team, position) %>%\n  filter<\/span> (points == max(points, na.rm= TRUE<\/span> ))\n\n# A tibble: 5 x 3\n# Groups: team, position [4]\n  team position points\n       \n1 AG 12.0\n2AF 19.0\n3 BG 34.0\n4 BG 34.0\n5BF 39.0<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043c\u0435\u0440 3. \u0412\u043e\u0437\u0432\u0440\u0430\u0442 \u043e\u0434\u043d\u043e\u0439 \u0441\u0442\u0440\u043e\u043a\u0438, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0435\u0439 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u0433\u0440\u0443\u043f\u043f\u044b.<\/strong><\/span><\/h3>\n
 \u0412 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u0431\u044b\u043b\u043e \u0434\u0432\u0430 \u0438\u0433\u0440\u043e\u043a\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043d\u0430\u0431\u0440\u0430\u043b\u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043e\u0447\u043a\u043e\u0432 \u0432 \u043a\u043e\u043c\u0430\u043d\u0434\u0435 A \u0438 \u043e\u0431\u0430 \u043d\u0430\u0445\u043e\u0434\u0438\u043b\u0438\u0441\u044c \u0432 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 G. \u0415\u0441\u043b\u0438 \u0432\u044b \u0445\u043e\u0442\u0438\u0442\u0435 \u0432\u0435\u0440\u043d\u0443\u0442\u044c \u0432 \u0433\u0440\u0443\u043f\u043f\u0443 \u0442\u043e\u043b\u044c\u043a\u043e \u043f\u0435\u0440\u0432\u043e\u0433\u043e \u0438\u0433\u0440\u043e\u043a\u0430 \u0441 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u043c \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435\u043c, \u0432\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u0440\u0435\u0437( ) \u0444\u0443\u043d\u043a\u0446\u0438\u044f.<\/strong> \u0434\u0435\u0439\u0441\u0442\u0432\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c:<\/span><\/p>\n
 library(dplyr)<\/span>\n\n#find rows that contain max points by team and position<\/span>\ndf %>%\n  group_by<\/span> (team, position) %>%\n  slice<\/span> (which.max(points))\n\n# A tibble: 4 x 3\n# Groups: team, position [4]\n  team position points\n       \n1AF 19.0\n2 AG 12.0\n3 BF 39.0\n4 BG 34.0<\/strong><\/pre>\n
 \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
 \u041f\u043e\u043b\u043d\u043e\u0435 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u043e: \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0441\u0443\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 R<\/a>
 \u041a\u0430\u043a \u0444\u0438\u043b\u044c\u0442\u0440\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u0440\u043e\u043a\u0438 \u0432 R<\/a>
 \u041a\u0430\u043a \u0443\u0434\u0430\u043b\u0438\u0442\u044c \u043f\u043e\u0432\u0442\u043e\u0440\u044f\u044e\u0449\u0438\u0435\u0441\u044f \u0441\u0442\u0440\u043e\u043a\u0438 \u0432 R<\/p>\n","protected":false},"excerpt":{"rendered":"
\u0427\u0430\u0441\u0442\u043e \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \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 \u043a\u0430\u0436\u0434\u043e\u0439 \u0433\u0440\u0443\u043f\u043f\u044b \u0432\u043e \u0444\u0440\u0435\u0439\u043c\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 R. \u041a \u0441\u0447\u0430\u0441\u0442\u044c\u044e, \u044d\u0442\u043e \u043b\u0435\u0433\u043a\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043f\u0430\u043a\u0435\u0442\u0430 dplyr . \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 \u044d\u0442\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445: #create data frame df <- data.frame(team = c(‘A’, ‘A’, ‘A’, ‘B’, ‘B’, ‘B’, ‘B’), position = c(‘G’, ‘F’, ‘F’, […]<\/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-955","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\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 \u043d\u0430 \u0433\u0440\u0443\u043f\u043f\u0443 \u0432 R - Statorials<\/title>\n<meta name=\"description\" content=\"\u041f\u0440\u043e\u0441\u0442\u043e\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0442\u043e\u0433\u043e, \u043a\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 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0433\u0440\u0443\u043f\u043f\u044b \u0432\u043e \u0444\u0440\u0435\u0439\u043c\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 R.\" \/>\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\/\u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435-\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435-\u043d\u0430-\u0433\u0440\u0443\u043f\u043f\u0443-r\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a 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content=\"https:\/\/statorials.org\/ru\/\u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435-\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435-\u043d\u0430-\u0433\u0440\u0443\u043f\u043f\u0443-r\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T04:39:16+00:00\" \/>\n<meta name=\"author\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e \u0430\u0432\u0442\u043e\u0440\u043e\u043c\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u043c\u0435\u0440\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f 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