<\/p>\n
Genellikle R’de grup ba\u015f\u0131na toplam\u0131 hesaplamak isteyebilirsiniz. Bunu yapmak i\u00e7in \u00fc\u00e7 y\u00f6ntem kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: R taban\u0131n\u0131 kullan\u0131n.<\/strong><\/span><\/p>\n Y\u00f6ntem 2: dplyr() paketini kullan\u0131n.<\/strong><\/span><\/p>\n Y\u00f6ntem 3: data.table paketini kullan\u0131n.<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler bu y\u00f6ntemlerin her birinin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesinde ekibin att\u0131\u011f\u0131 puanlar\u0131n toplam\u0131n\u0131 hesaplamak i\u00e7in R veritaban\u0131n\u0131n Aggregate()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesinde tak\u0131m\u0131n kazand\u0131\u011f\u0131 puanlar\u0131n toplam\u0131n\u0131 hesaplamak i\u00e7in dplyr<\/strong> paketinin group_by()<\/strong> ve summarise()<\/strong> i\u015flevlerinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesinde tak\u0131m\u0131n att\u0131\u011f\u0131 puanlar\u0131n toplam\u0131n\u0131 hesaplamak i\u00e7in data.table<\/strong> paketinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Her \u00fc\u00e7 y\u00f6ntemin de ayn\u0131 sonu\u00e7lar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/span><\/p>\n Not:<\/strong> \u00c7ok b\u00fcy\u00fck bir veri k\u00fcmeniz varsa, data.table y\u00f6ntemi burada listelenen \u00fc\u00e7 y\u00f6ntemden en h\u0131zl\u0131 \u015fekilde \u00e7al\u0131\u015facakt\u0131r.<\/span><\/p>\n R’de grup ba\u015f\u0131na ortalama nas\u0131l hesaplan\u0131r<\/a> Genellikle R’de grup ba\u015f\u0131na toplam\u0131 hesaplamak isteyebilirsiniz. Bunu yapmak i\u00e7in \u00fc\u00e7 y\u00f6ntem kullanabilirsiniz: Y\u00f6ntem 1: R taban\u0131n\u0131 kullan\u0131n. aggregate(df$col_to_aggregate, list(df$col_to_group_by), FUN= sum ) Y\u00f6ntem 2: dplyr() paketini kullan\u0131n. library (dplyr) df %>% group_by (col_to_group_by) %>% summarize (Freq = sum (col_to_aggregate)) Y\u00f6ntem 3: data.table paketini kullan\u0131n. library (data.table) dt[ ,list(sum= sum (col_to_aggregate)), by=col_to_group_by] A\u015fa\u011f\u0131daki \u00f6rnekler bu […]<\/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-1765","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n aggregate(df$col_to_aggregate, list(df$col_to_group_by), FUN= sum<\/span> )<\/span><\/strong><\/pre>\n library<\/span> (dplyr)\n\ndf %>%\n group_by<\/span> (col_to_group_by) %>%\n summarize<\/span> (Freq = sum<\/span> (col_to_aggregate))\n<\/b><\/span><\/pre>\n library<\/span> (data.table)\n\ndt[ ,list(sum= sum<\/span> (col_to_aggregate)), by=col_to_group_by]\n<\/b><\/span><\/pre>\n Y\u00f6ntem 1: R taban\u0131n\u0131 kullanarak grup ba\u015f\u0131na toplam\u0131 hesaplay\u0131n<\/strong><\/span><\/h3>\n
#create data frame<\/span>\ndf <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),\n pts=c(5, 8, 14, 18, 5, 7, 7),\n rebs=c(8, 8, 9, 3, 8, 7, 4))\n\n#view data frame<\/span>\ndf\n\n team pts rebs\n1 to 5 8\n2 to 8 8\n3 b 14 9\n4 b 18 3\n5 b 5 8\n6 c 7 7\n7 c 7 4\n\n#find sum of points scored by team\n<\/span><\/span>aggregate(df$pts, list(df$team), FUN= sum<\/span> )\n\n Group.1 x\n1 to 13\n2 b 37\n3 v 14\n<\/span><\/strong><\/pre>\n Y\u00f6ntem 2: dplyr kullanarak toplam\u0131 gruba g\u00f6re hesaplay\u0131n<\/strong><\/span><\/h3>\n
library<\/span> (dplyr)<\/span><\/b>\n\n#create data frame<\/span>\ndf <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),\n pts=c(5, 8, 14, 18, 5, 7, 7),\n rebs=c(8, 8, 9, 3, 8, 7, 4))\n\n#find sum of points scored by team<\/span>\ndf %>%\ngroup_by<\/span> (team) %>%\nsummarize<\/span> (Freq = sum<\/span> (pts))\n\n# A tibble: 3 x 2\n team Freq\n <chr> <dbl>\n1 to 13\n2 b 37\n3 v 14<\/b>\n<\/span><\/strong><\/pre>\n Y\u00f6ntem 3: data.table’\u0131 kullanarak toplam\u0131 gruba g\u00f6re hesaplay\u0131n<\/strong><\/span><\/h3>\n
library<\/span> (data.table)<\/span><\/b>\n\n#create data frame<\/span>\ndf <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),\n pts=c(5, 8, 14, 18, 5, 7, 7),\n rebs=c(8, 8, 9, 3, 8, 7, 4))\n\n#convert data frame to data table<\/span> \nsetDT(df)\n\n#find sum of points scored by team<\/span>\ndf[,list(sum= sum<\/span> (pts)), by=team]\n\n team sum\n1:a 13\n2:b37\n3:c14<\/b><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
R’de gruba g\u00f6re nicelikler nas\u0131l hesaplan\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"