<\/p>\n
R’deki gruba g\u00f6re standart sapmay\u0131 hesaplamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: R taban\u0131n\u0131 kullan\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 2: dplyr’\u0131 kullan\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 3: data.table’\u0131 kullanma<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler, R’deki a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesiyle bu y\u00f6ntemlerin her birinin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, tak\u0131m taraf\u0131ndan at\u0131lan puanlar\u0131n standart sapmas\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, tak\u0131m taraf\u0131ndan at\u0131lan puanlar\u0131n standart sapmas\u0131n\u0131 hesaplamak i\u00e7in dplyr<\/strong> paketindeki group_by<\/strong> ()<\/strong> ve summarise_at()<\/strong> i\u015flevlerinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, data.table<\/strong> paketindeki i\u015flevleri kullanarak tak\u0131m taraf\u0131ndan at\u0131lan puanlar\u0131n standart sapmas\u0131n\u0131n nas\u0131l hesaplanaca\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> : A\u015f\u0131r\u0131 b\u00fcy\u00fck bir veri \u00e7er\u00e7evesiyle \u00e7al\u0131\u015f\u0131yorsan\u0131z, bu paketler R taban\u0131na g\u00f6re \u00e7ok daha h\u0131zl\u0131 \u00e7al\u0131\u015ft\u0131\u011f\u0131ndan dplyr<\/strong> veya data.table<\/strong> yakla\u015f\u0131m\u0131n\u0131 kullanman\u0131z \u00f6nerilir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde R’de di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n R’de grup ba\u015f\u0131na ortalama nas\u0131l hesaplan\u0131r<\/a> R’deki gruba g\u00f6re standart sapmay\u0131 hesaplamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz: Y\u00f6ntem 1: R taban\u0131n\u0131 kullan\u0131n aggregate(df$col_to_aggregate, list(df$col_to_group_by), FUN=sd) Y\u00f6ntem 2: dplyr’\u0131 kullan\u0131n library (dplyr) df %>% group_by(col_to_group_by) %>% summarise_at(vars(col_to_aggregate), list(name=sd)) Y\u00f6ntem 3: data.table’\u0131 kullanma library (data.table) setDT(df) dt[ ,list(sd=sd(col_to_aggregate)), by=col_to_group_by] A\u015fa\u011f\u0131daki \u00f6rnekler, R’deki a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesiyle bu y\u00f6ntemlerin her birinin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 […]<\/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-3786","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=sd)<\/strong><\/span><\/pre>\n library<\/span> (dplyr)\n\ndf %>%\n group_by(col_to_group_by) %>%\n summarise_at(vars(col_to_aggregate), list(name=sd))\n<\/span><\/b><\/span><\/pre>\n library<\/span> (data.table)\n\nsetDT(df)\n\ndt[ ,list(sd=sd(col_to_aggregate)), by=col_to_group_by]\n<\/span><\/b><\/span><\/pre>\n #create data frame\n<\/span>df <- data. frame<\/span> (team=rep(c(' A<\/span> ', ' B<\/span> ', ' C<\/span> '), each= 6<\/span> ),\n points=c(8, 10, 12, 12, 14, 15, 10, 11, 12,\n 18, 22, 24, 3, 5, 5, 6, 7, 9))\n\n#view data frame\n<\/span>df\n\n team points\n1 to 8\n2 to 10\n3 to 12\n4 to 12\n5 to 14\n6 to 15\n7 B 10\n8 B 11\n9 B 12\n10 B 18\n11 B 22\n12 B 24\n13 C 3\n14 C 5\n15 C 5\n16 C 6\n17 C 7\n18 C 9<\/b><\/span><\/pre>\n Y\u00f6ntem 1: R taban\u0131n\u0131 kullanarak standart sapmay\u0131 gruba g\u00f6re hesaplay\u0131n<\/strong><\/span><\/h2>\n
#calculate standard deviation of points by team\n<\/span>aggregate(df$points, list(df$team), FUN=sd)\n\n Group.1 x\n1 A 2.562551\n2 B 6.013873\n3 C 2.041241<\/span><\/strong><\/pre>\n Y\u00f6ntem 2:<\/strong><\/span> dplyr kullanarak gruba g\u00f6re<\/strong><\/span> standart sapmay\u0131<\/strong><\/span> hesaplama<\/h2>\n
library<\/span> (dplyr)<\/b><\/span><\/span>\n\n#calculate standard deviation of points scored by team<\/span>\ndf %>%\n group_by(team) %>%\n summarise_at(vars(points), list(name=sd))\n\n<\/b># A tibble: 3 x 2\n team name\n \n1 to 2.56\n2 B 6.01\n3C 2.04\n<\/span><\/strong><\/pre>\n Y\u00f6ntem 3: data.table’\u0131 kullanarak gruba g\u00f6re standart sapmay\u0131 hesaplay\u0131n<\/strong><\/span><\/h2>\n
library<\/span> (data.table)<\/b>\n<\/span><\/span>\n#convert data frame to data table<\/span> \nsetDT(df)\n\n#calculate standard deviation of points scored by team<\/span>\ndf[,list(sd=sd(points)), by=team]\n<\/span>\n team sd\n1: A 2.562551\n2: B 6.013873\n3:C2.041241<\/b><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
R’de gruba g\u00f6re toplam nas\u0131l hesaplan\u0131r<\/a>
R’de gruba g\u00f6re nicelikler nas\u0131l hesaplan\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"