Ancak R’deki veri \u00e7er\u00e7eveleri, dizin s\u00fctunuyla ayn\u0131 i\u015flevi g\u00f6ren sat\u0131r adlar\u0131na<\/strong> sahiptir.<\/span><\/p>\n Mevcut bir veri \u00e7er\u00e7evesi s\u00fctununu R’deki bir veri \u00e7er\u00e7evesi i\u00e7in sat\u0131r adlar\u0131 olarak ayarlamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: R Taban\u0131n\u0131 Kullanarak Sat\u0131r Adlar\u0131n\u0131 Ayarlama<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Tidyverse paketini kullanarak sat\u0131r adlar\u0131n\u0131 ayarlama<\/strong><\/span><\/p>\n Y\u00f6ntem 3: Verileri \u0130\u00e7eri Aktar\u0131rken Sat\u0131r Adlar\u0131n\u0131 Ayarlama<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler her y\u00f6ntemin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n R’de a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n ID s\u00fctununu sat\u0131r ad\u0131 olarak ayarlamak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Kimlik s\u00fctunundaki de\u011ferler art\u0131k veri \u00e7er\u00e7evesinin sat\u0131r adlar\u0131d\u0131r.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, sat\u0131r adlar\u0131n\u0131 veri \u00e7er\u00e7evesindeki kimlik s\u00fctununa e\u015fitlemek i\u00e7in Spiceverse<\/strong> paketinin s\u00fctun_to_rownames()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Bu sonucun \u00f6nceki \u00f6rnekle e\u015fle\u015fti\u011fini unutmay\u0131n.<\/span><\/p>\n Diyelim ki my_data.csv<\/strong> ad\u0131nda a\u015fa\u011f\u0131daki CSV dosyam\u0131z var:<\/span> <\/p>\n CSV dosyas\u0131n\u0131 i\u00e7e aktarmak ve i\u00e7e aktarma s\u0131ras\u0131nda sat\u0131r adlar\u0131n\u0131 kimlik s\u00fctununa e\u015fit olacak \u015fekilde ayarlamak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Kimlik s\u00fctunundaki de\u011ferlerin veri \u00e7er\u00e7evesinde sat\u0131r ad\u0131 olarak kullan\u0131ld\u0131\u011f\u0131na dikkat edin.<\/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 Ko\u015fula ba\u011fl\u0131 olarak R’deki veri \u00e7er\u00e7evesinden sat\u0131rlar nas\u0131l kald\u0131r\u0131l\u0131r<\/a> R’deki veri \u00e7er\u00e7eveleri, pandalardaki veri \u00e7er\u00e7eveleri gibi bir “indeks” s\u00fctununa sahip de\u011fildir. Ancak R’deki veri \u00e7er\u00e7eveleri, dizin s\u00fctunuyla ayn\u0131 i\u015flevi g\u00f6ren sat\u0131r adlar\u0131na sahiptir. Mevcut bir veri \u00e7er\u00e7evesi s\u00fctununu R’deki bir veri \u00e7er\u00e7evesi i\u00e7in sat\u0131r adlar\u0131 olarak ayarlamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz: Y\u00f6ntem 1: R Taban\u0131n\u0131 Kullanarak Sat\u0131r Adlar\u0131n\u0131 Ayarlama #set specific column […]<\/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-3089","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n #set specific column as row names\n<\/span>rownames(df) <- df$my_column\n\n#remove original column from data frame\n<\/span>df$my_column <- NULL<\/strong><\/pre>\n library<\/span> (tidyverse)<\/span>\n\n<\/span>#set specific column as row names<\/span>\ndf <- df %>% column_to_rownames(., var = ' my_column<\/span> ')\n<\/strong><\/pre>\n #import CSV file and specify column to use as row names<\/span>\ndf <- read. csv<\/span> (' my_data.csv<\/span> ', row.names<\/span> =' my_column<\/span> ')<\/strong><\/pre>\n \u00d6rnek 1: Base R’yi kullanarak sat\u0131r adlar\u0131n\u0131 tan\u0131mlama<\/strong><\/span><\/h3>\n
#create data frame\ndf <- data. frame<\/span> (ID=c(101, 102, 103, 104, 105),\n points=c(99, 90, 86, 88, 95),\n assists=c(33, 28, 31, 39, 34),\n rebounds=c(30, 28, 24, 24, 28))\n\n#view data frame\n<\/span>df\n\n ID points assists rebounds\n1 101 99 33 30\n2 102 90 28 28\n3 103 86 31 24\n4 104 88 39 24\n5 105 95 34 28<\/span><\/span><\/strong><\/pre>\n #set ID column as row names\n<\/span>rownames(df) <- df$ID\n\n#remove original ID column from data frame\n<\/span>df$ID <- NULL\n\n#view updated data frame\n<\/span>df\n\n points assists rebounds\n101 99 33 30\n102 90 28 28\n103 86 31 24\n104 88 39 24\n105 95 34 28\n<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 2: Tidyverse paketini kullanarak sat\u0131r adlar\u0131n\u0131 ayarlama<\/strong><\/span><\/h3>\n
library<\/span> (tidyverse)<\/span>\n\n#create data frame\ndf <- data. frame<\/span> (ID=c(101, 102, 103, 104, 105),\n points=c(99, 90, 86, 88, 95),\n assists=c(33, 28, 31, 39, 34),\n rebounds=c(30, 28, 24, 24, 28))\n\n#set ID column as row names<\/span>\ndf <- df %>% column_to_rownames(., var = ' ID<\/span> ')\n\n#view updated data frame<\/span>\ndf\n\n points assists rebounds\n101 99 33 30\n102 90 28 28\n103 86 31 24\n104 88 39 24\n105 95 34 28\n<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 3: Verileri i\u00e7e aktar\u0131rken sat\u0131r adlar\u0131n\u0131 ayarlay\u0131n<\/strong><\/span><\/h3>\n
![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/indexcol1.jpg\")
<\/p>\n #import CSV file and specify ID column to use as row names<\/span>\ndf <- read. csv<\/span> (' my_data.csv<\/span> ', row.names<\/span> =' ID<\/span> ')\n\n#view data frame<\/span>\ndf\n\n points assists rebounds\n101 99 33 30\n102 90 28 28\n103 86 31 24\n104 88 39 24\n105 95 34 28\n<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
R’de veri \u00e7er\u00e7evesindeki de\u011ferler nas\u0131l de\u011fi\u015ftirilir?<\/a>
R’deki veri \u00e7er\u00e7evesinden s\u00fctunlar nas\u0131l kald\u0131r\u0131l\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"