<\/p>\n
Bazen g\u00fcnl\u00fck verileri R’de haftal\u0131k, ayl\u0131k veya y\u0131ll\u0131k veriler halinde toplamak isteyebilirsiniz.<\/span><\/p>\n Bu e\u011fitimde lubridate<\/strong> ve dplyr<\/strong> paketlerini kullanarak bunun nas\u0131l kolayca yap\u0131laca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n R’de bir \u00fcr\u00fcn\u00fcn ard\u0131\u015f\u0131k 100 g\u00fcnl\u00fck bir s\u00fcre boyunca g\u00fcnl\u00fck sat\u0131\u015flar\u0131n\u0131 g\u00f6steren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Bu verileri toplamak i\u00e7in lubridate<\/strong> paketinin a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanan Floor_date()<\/a> fonksiyonunu kullanabiliriz:<\/span><\/p>\n Alt\u0131n:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod par\u00e7ac\u0131klar\u0131, haftaya, aya ve y\u0131la g\u00f6re ortalama sat\u0131\u015flar\u0131 bulmak i\u00e7in bu i\u015flevin dplyr<\/strong> paketindeki group_by()<\/a> ve Summary()<\/a> i\u015flevleriyle nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Haftal\u0131k ortalama sat\u0131\u015flar<\/strong><\/span><\/p>\n Ayl\u0131k ortalama sat\u0131\u015f<\/strong><\/span><\/p>\n Y\u0131ll\u0131k ortalama sat\u0131\u015f<\/strong><\/span><\/p>\n Ortalamaya g\u00f6re toplamay\u0131 se\u00e7ti\u011fimizi ancak medyan, mod, maksimum, minimum vb. gibi istedi\u011fimiz herhangi bir \u00f6zet istatisti\u011fi kullanabilece\u011fimizi 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 R’de grup ba\u015f\u0131na ortalama nas\u0131l hesaplan\u0131r<\/a> Bazen g\u00fcnl\u00fck verileri R’de haftal\u0131k, ayl\u0131k veya y\u0131ll\u0131k veriler halinde toplamak isteyebilirsiniz. Bu e\u011fitimde lubridate ve dplyr paketlerini kullanarak bunun nas\u0131l kolayca yap\u0131laca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r. \u00d6rnek: G\u00fcnl\u00fck verileri R’de toplama R’de bir \u00fcr\u00fcn\u00fcn ard\u0131\u015f\u0131k 100 g\u00fcnl\u00fck bir s\u00fcre boyunca g\u00fcnl\u00fck sat\u0131\u015flar\u0131n\u0131 g\u00f6steren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m: #make this example reproducible set.seed(1) #create data frame […]<\/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-1107","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: G\u00fcnl\u00fck verileri R’de toplama<\/strong><\/h2>\n
#make this example reproducible\n<\/span>set.seed(1)\n\n#create data frame<\/span>\ndf <- data.frame(date = as.Date<\/span> (\" 2020-12-01<\/span> \") + 0:99,\n sales = runif<\/span> (100, 20, 50))\n\n#view first six rows<\/span>\nhead(df)\n\n dirty date\n1 2020-12-01 27.96526\n2 2020-12-02 31.16372\n3 2020-12-03 37.18560\n4 2020-12-04 47.24623\n5 2020-12-05 26.05046\n6 2020-12-06 46.95169<\/strong><\/pre>\n floor_date<\/span> (x, unit)<\/span><\/strong><\/pre>\n\n
library<\/span> (lubridate)<\/span>\nlibrary<\/span> (dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$week <- floor_date<\/span> (df$date, \" week<\/span> \")\n\n#find average sales per week\ndf %>%\n group_by<\/span> (week) %>%\n summarize<\/span> (mean = mean<\/span> (sales))<\/span><\/span>\n\n# A tibble: 15 x 2\n week means\n \n 1 2020-11-29 33.9\n 2 2020-12-06 35.3\n 3 2020-12-13 39.0\n 4 2020-12-20 34.4\n 5 2020-12-27 33.6\n 6 2021-01-03 35.9\n 7 2021-01-10 37.8\n 8 2021-01-17 36.8\n 9 2021-01-24 32.8\n10 2021-01-31 33.9\n11 2021-02-07 34.1\n12 2021-02-14 41.6\n13 2021-02-21 31.8\n14 2021-02-28 35.2\n15 2021-03-07 37.1<\/span><\/span><\/span><\/strong><\/pre>\n library<\/span> (lubridate)<\/span>\nlibrary<\/span> (dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$month <- floor_date<\/span> (df$date, \" month<\/span> \")\n\n#find average sales by month\ndf %>%<\/span>\n group_by<\/span> (month) %>%<\/span>\n summarize<\/span> (mean =<\/span> mean<\/span> (sales))<\/span><\/span>\n\n# A tibble: 4 x 2\n month mean\n \n1 2020-12-01 35.3\n2 2021-01-01 35.6\n3 2021-02-01 35.2\n4 2021-03-01 37.0\n<\/span><\/span><\/span><\/strong><\/pre>\n library<\/span> (lubridate)<\/span>\nlibrary<\/span> (dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$year <- floor_date<\/span> (df$date, \" year<\/span> \")\n\n#find average sales by month\ndf %>%<\/span>\n group_by<\/span> (year) %>%<\/span>\n summarize<\/span> (mean =<\/span> mean<\/span> (sales))\n\n# A tibble: 2 x 2\n year means\n \n1 2020-01-01 35.3\n2 2021-01-01 35.7<\/span><\/span>\n<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
R’de k\u00fcm\u00fclatif toplamlar nas\u0131l hesaplan\u0131r<\/a>
R’de bir zaman serisi nas\u0131l \u00e7izilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"