<\/p>\n
Grup ba\u015f\u0131na bir de\u011fi\u015fkeni \u00f6zetlemek i\u00e7in group_by()<\/strong> i\u015flevini kulland\u0131ktan sonra sat\u0131rlar\u0131n grubunu \u00e7\u00f6zmek i\u00e7in dplyr’deki ungroup()<\/strong> i\u015flevini kullanabilirsiniz.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekte bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131 g\u00f6sterilmektedir.<\/span><\/p>\n R’de a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n \u015eimdi, tak\u0131ma<\/strong> g\u00f6re grupland\u0131r\u0131lm\u0131\u015f ortalama puan<\/strong> de\u011ferini hesaplamak i\u00e7in a\u015fa\u011f\u0131daki kodu kulland\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n Bu s\u00f6zdizimini kullanarak tak\u0131ma<\/strong> g\u00f6re grupland\u0131r\u0131lm\u0131\u015f puanlar\u0131n<\/strong> ortalama de\u011ferini hesaplayabiliriz, ancak asistler<\/strong> s\u00fctununu kaybettik.<\/span><\/p>\n Yard\u0131mc\u0131lar<\/strong> s\u00fctununu korumak i\u00e7in, Summary()<\/strong> yerine mutate()<\/strong> kullanabiliriz ve sonunda hala ungroup() i\u015flevini<\/strong> kullanabiliriz:<\/span><\/p>\n Bu kez asist<\/strong> s\u00fctununu koruyabildik ve mutate()<\/strong> i\u015flevini kullanarak her tak\u0131m\u0131n ortalama puan de\u011ferini g\u00f6steren Mean_points<\/strong> ad\u0131nda yeni bir s\u00fctun ekledik.<\/span><\/span><\/p>\n Ungroup()<\/strong> fonksiyonunu da kulland\u0131\u011f\u0131m\u0131z i\u00e7in grupland\u0131r\u0131lm\u0131\u015f de\u011fi\u015fkenlerden etkilenen hesaplamalar konusunda endi\u015felenmeden bu yeni veri \u00e7er\u00e7evesi \u00fczerinde hesaplamalar ger\u00e7ekle\u015ftirebiliyoruz.<\/span><\/p>\n ungroup()<\/strong> i\u015flevini kullanmasayd\u0131k, veri \u00e7er\u00e7evesindeki sat\u0131rlar yine birlikte grupland\u0131r\u0131l\u0131rd\u0131 ve bu, daha sonra ba\u015fka hesaplamalar yapt\u0131\u011f\u0131m\u0131zda istenmeyen sonu\u00e7lara yol a\u00e7abilirdi.<\/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 Dplyr kullanarak benzersiz de\u011ferler nas\u0131l filtrelenir<\/a> Grup ba\u015f\u0131na bir de\u011fi\u015fkeni \u00f6zetlemek i\u00e7in group_by() i\u015flevini kulland\u0131ktan sonra sat\u0131rlar\u0131n grubunu \u00e7\u00f6zmek i\u00e7in dplyr’deki ungroup() i\u015flevini kullanabilirsiniz. A\u015fa\u011f\u0131daki \u00f6rnekte bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131 g\u00f6sterilmektedir. \u00d6rnek: dplyr’de ungroup() nas\u0131l kullan\u0131l\u0131r? R’de a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m: #create data frame df <- data. frame (team=c(‘A’, ‘A’, ‘A’, ‘B’, ‘B’, ‘B’), dots=c(14, 18, 22, 26, […]<\/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-3554","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: dplyr’de ungroup() nas\u0131l kullan\u0131l\u0131r?<\/strong><\/span><\/h2>\n
#create data frame\n<\/span>df <- data. frame<\/span> (team=c('A', 'A', 'A', 'B', 'B', 'B'),\n dots=c(14, 18, 22, 26, 36, 34),\n assists=c(5, 4, 4, 8, 7, 3))\n\n#view data frame\n<\/span>df\n\n team points assists\n1 to 14 5\n2 to 18 4\n3 to 22 4\n4 B 26 8\n5 B 36 7\n6 B 34 3<\/strong><\/span><\/pre>\n library<\/span> (dplyr)<\/span>\n\n#calculate mean of points, grouped by team\ndf_new <- df %>%\n group_by(team) %>%\n summarize(mean_points = mean(points)) %>%\n A group()\n\n#view results<\/span>\ndf_new\n\n# A tibble: 2 x 2\n team mean_points\n \n1 to 18\n2 B 32\n<\/span><\/span><\/strong><\/pre>\n library<\/span> (dplyr)<\/span>\n\n#calculate mean of points, grouped by team\ndf_new <- df %>%\n group_by(team) %>%\n mutate(mean_points = mean(points)) %>%\n A group()\n\n#view results\n<\/span>df_new\n\n# A tibble: 6 x 4\n team points assists mean_points\n \n1 A 14 5 18\n2 A 18 4 18\n3 A 22 4 18\n4 B 26 8 32\n5 B 36 7 32\n6 B 34 3 32\n<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Dplyr kullanarak birden \u00e7ok ko\u015fula g\u00f6re filtreleme nas\u0131l yap\u0131l\u0131r
R’deki s\u00fctunlardaki olu\u015fum say\u0131s\u0131 nas\u0131l say\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"