{"id":2219,"date":"2023-07-23T05:12:02","date_gmt":"2023-07-23T05:12:02","guid":{"rendered":"https:\/\/statorials.org\/tr\/r-istatistikleri-gruba-gore-ozetleme\/"},"modified":"2023-07-23T05:12:02","modified_gmt":"2023-07-23T05:12:02","slug":"r-istatistikleri-gruba-gore-ozetleme","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/r-istatistikleri-gruba-gore-ozetleme\/","title":{"rendered":"R'de gruba g\u00f6re \u00f6zet istatistikler nas\u0131l hesaplan\u0131r"},"content":{"rendered":"

<\/p>\n

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R’de grup \u00f6zet istatistiklerini hesaplaman\u0131n iki temel yolu vard\u0131r:<\/span><\/p>\n

Y\u00f6ntem 1: Base R’den tapply() i\u015flevini kullan\u0131n<\/strong><\/span><\/p>\n

 tapply(df$value_col, df$group_col, summary)\n<\/strong><\/pre>\n
 Y\u00f6ntem 2: dplyr paketindeki group_by() i\u015flevini kullan\u0131n<\/strong><\/span><\/p>\n
 library<\/span> (dplyr)\n\ndf %>%\n  group_by<\/span> (group_col) %>% \n  summarize<\/span> (min = min(value_col),\n            q1 = quantile(value_col, 0.25<\/span> ),\n            median = median(value_col),\n            mean = mean(value_col),\n            q3 = quantile(value_col, 0.75<\/span> ),\n            max = max(value_col))<\/strong><\/span><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnekler her y\u00f6ntemin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n
 Y\u00f6ntem 1: Base R’den tapply() i\u015flevini kullan\u0131n<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, \u00f6zet istatistikleri gruba g\u00f6re hesaplamak i\u00e7in R’deki tapply()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),\n                 points=c(99, 68, 86, 88, 95, 74, 78, 93),\n                 assists=c(22, 28, 31, 35, 34, 45, 28, 31),\n                 rebounds=c(30, 28, 24, 24, 30, 36, 30, 29))\n\n#calculate summary statistics of 'points' grouped by 'team'\n<\/span>tapply(df$points, df$team, summary)\n\n$A\n   Min. 1st Qu. Median Mean 3rd Qu. Max. \n  68.00 81.50 87.00 85.25 90.75 99.00 \n\n$B\n   Min. 1st Qu. Median Mean 3rd Qu. Max. \n   74.0 77.0 85.5 85.0 93.5 95.0 \n<\/span><\/span><\/strong><\/pre>\n
 Y\u00f6ntem 2: dplyr paketindeki group_by() i\u015flevini kullan\u0131n<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, \u00f6zet istatistikleri gruba g\u00f6re hesaplamak i\u00e7in dplyr<\/a> paketindeki group_by()<\/strong> ve Summary()<\/strong> i\u015flevlerinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 library<\/span> (dplyr)<\/span>\n\n#create data frame\n<\/span>df <- data. frame<\/span> (team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),\n                 points=c(99, 68, 86, 88, 95, 74, 78, 93),\n                 assists=c(22, 28, 31, 35, 34, 45, 28, 31),\n                 rebounds=c(30, 28, 24, 24, 30, 36, 30, 29))\n\n#calculate summary statistics of 'points' grouped by 'team'\n<\/span>df %>%\n  group_by<\/span> (team) %>% \n  summarize<\/span> (min = min(points),\n            q1 = quantile(points, 0.25<\/span> ),\n            median = median(points),\n            mean = mean(points),\n            q3 = quantile(points, 0.75<\/span> ),\n            max = max(points))\n\n# A tibble: 2 x 7\n  team min q1 median mean q3 max\n         \n1 A 68 81.5 87 85.2 90.8 99\n2 B 74 77 85.5 85 93.5 95\n<\/span><\/span><\/strong><\/pre>\n
 Her iki y\u00f6ntemin de tamamen ayn\u0131 sonu\u00e7lar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/span><\/p>\n
 Dplyr yakla\u015f\u0131m\u0131n\u0131n daha b\u00fcy\u00fck veri \u00e7er\u00e7eveleri i\u00e7in muhtemelen daha h\u0131zl\u0131 olaca\u011f\u0131n\u0131, ancak her iki y\u00f6ntemin de daha k\u00fc\u00e7\u00fck veri \u00e7er\u00e7evelerinde benzer \u015fekilde performans g\u00f6sterece\u011fini belirtmekte fayda var.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki e\u011fitimlerde R’de di\u011fer ortak gruplama i\u015flevlerinin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n
 R’de gruba g\u00f6re frekans tablosu nas\u0131l olu\u015fturulur<\/a>
 R’de gruba g\u00f6re toplam nas\u0131l hesaplan\u0131r<\/a>
 R’de grup ba\u015f\u0131na ortalama nas\u0131l hesaplan\u0131r<\/a>
 R’de gruba g\u00f6re toplam nas\u0131l hesaplan\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
R’de grup \u00f6zet istatistiklerini hesaplaman\u0131n iki temel yolu vard\u0131r: Y\u00f6ntem 1: Base R’den tapply() i\u015flevini kullan\u0131n tapply(df$value_col, df$group_col, summary) Y\u00f6ntem 2: dplyr paketindeki group_by() i\u015flevini kullan\u0131n library (dplyr) df %>% group_by (group_col) %>% summarize (min = min(value_col), q1 = quantile(value_col, 0.25 ), median = median(value_col), mean = mean(value_col), q3 = quantile(value_col, 0.75 ), max = […]<\/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-2219","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nR - Statorials'de gruba g\u00f6re \u00f6zet istatistikler nas\u0131l hesaplan\u0131r<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde R'de grup \u00f6zet istatistiklerinin nas\u0131l hesaplanaca\u011f\u0131 \u00e7e\u015fitli \u00f6rneklerle a\u00e7\u0131klanmaktad\u0131r.\" \/>\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\/tr\/r-istatistikleri-gruba-gore-ozetleme\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R - 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