<\/p>\n
Bir veri \u00e7er\u00e7evesindeki sat\u0131rlar\u0131 dplyr kullanarak ada g\u00f6re se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n R’de a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Sat\u0131r ad\u0131 Hawks, Cavs veya Heat’e e\u015fit olan sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n dplyr’\u0131n yaln\u0131zca adlar\u0131 filter()<\/strong> i\u015flevine sa\u011flad\u0131\u011f\u0131m\u0131z vekt\u00f6rde bulunan sat\u0131rlar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/span><\/span><\/p>\n Ayr\u0131ca adlar\u0131 bir vekt\u00f6rde yer almayan<\/strong> t\u00fcm sat\u0131rlar\u0131 se\u00e7mek i\u00e7in \u00fcnlem i\u015fareti ( !<\/strong> ) kullanabilece\u011finizi de unutmay\u0131n:<\/span><\/p>\n dplyr’\u0131n yaln\u0131zca adlar\u0131 filter()<\/strong> i\u015flevine sa\u011flad\u0131\u011f\u0131m\u0131z vekt\u00f6rde bulunmayan sat\u0131rlar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/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> Bir veri \u00e7er\u00e7evesindeki sat\u0131rlar\u0131 dplyr kullanarak ada g\u00f6re se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz: library (dplyr) #select rows by name df %>% filter(row. names (df) %in% c(‘ name1 ‘, ‘ name2 ‘, ‘ name3 ‘)) A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir. \u00d6rnek: dplyr kullanarak sat\u0131rlar\u0131 ada g\u00f6re se\u00e7in R’de a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu […]<\/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-3499","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n library<\/span> (dplyr)\n\n#select rows by name\n<\/span>df %>%\n filter(row. names<\/span> (df) %in% c(' name1<\/span> ', ' name2<\/span> ', ' name3<\/span> '))<\/strong><\/pre>\n \u00d6rnek: dplyr kullanarak sat\u0131rlar\u0131 ada g\u00f6re se\u00e7in<\/strong><\/span><\/h2>\n
#create data frame\n<\/span>df <- data. frame<\/span> (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 row names\n<\/span>row. names<\/span> (df) <- c('Mavs', 'Hawks', 'Cavs', 'Lakers', 'Heat')\n\n#view data frame\n<\/span>df\n\n points assists rebounds\nMavs 99 33 30\nHawks 90 28 28\nCavs 86 31 24\nLakers 88 39 24\nHeat 95 34 28\n<\/strong><\/span><\/pre>\n library<\/span> (dplyr)<\/span>\n\n#select specific rows by name\ndf %>%\n filter(row. names<\/span> (df) %in% c(' Hawks<\/span> ', ' Cavs<\/span> ', ' Heat<\/span> '))\n\n points assists rebounds\nHawks 90 28 28\nCavs 86 31 24\nHeat 95 34 28<\/span><\/span><\/strong><\/pre>\n library<\/span> (dplyr)<\/span>\n\n#select rows that do not have Hawks, Cavs, or Heat in the row name\ndf %>%\n filter(!(row. names<\/span> (df) %in% c(' Hawks<\/span> ', ' Cavs<\/span> ', ' Heat<\/span> ')))\n\n points assists rebounds\nMavs 99 33 30\nLakers 88 39 24<\/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":"