<\/p>\n
Verileri zamana g\u00f6re gruplamak ve R’de toplama i\u015flemini ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n Bu \u00f6zel \u00f6rnek, de\u011ferleri saate g\u00f6re Saat<\/strong> ad\u0131 verilen bir s\u00fctunda grupland\u0131r\u0131r ve ard\u0131ndan her saat i\u00e7in Sat\u0131\u015f<\/strong> s\u00fctunundaki de\u011ferlerin toplam\u0131n\u0131 hesaplar.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Bir ma\u011faza i\u00e7in g\u00fcn\u00fcn farkl\u0131 saatlerinde yap\u0131lan sat\u0131\u015flar\u0131n say\u0131s\u0131n\u0131 g\u00f6steren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Zaman<\/strong> s\u00fctununu saatlere g\u00f6re gruplamak ve her saate ili\u015fkin sat\u0131\u015f<\/strong> toplam\u0131n\u0131 hesaplamak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n Sonu\u00e7tan \u015funu g\u00f6rebiliriz:<\/span><\/p>\n Ba\u015fka bir toplama i\u015flemi de ger\u00e7ekle\u015ftirebilece\u011fimizi unutmay\u0131n.<\/span><\/p>\n \u00d6rne\u011fin saat ba\u015f\u0131na ortalama<\/strong> sat\u0131\u015f say\u0131s\u0131n\u0131 hesaplayabiliriz:<\/span><\/p>\n Sonu\u00e7tan \u015funu g\u00f6rebiliriz:<\/span><\/p>\n Kendi veri \u00e7er\u00e7evenizi zamana g\u00f6re gruplamaktan ve \u00f6zet()<\/strong> i\u015flevindeki metri\u011fi de\u011fi\u015ftirerek istedi\u011finiz herhangi bir metri\u011fi hesaplamaktan \u00e7ekinmeyin.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde R’de di\u011fer yayg\u0131n i\u015flemlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n R’de veriler aya g\u00f6re nas\u0131l gruplan\u0131r<\/a> Verileri zamana g\u00f6re gruplamak ve R’de toplama i\u015flemini ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz: library (dplyr) library (lubridate) #group by hours in time column and calculate sum of sales df %>% group_by(time=floor_date(time, ‘ 1 hour ‘)) %>% summarize(sum_sales=sum(sales)) Bu \u00f6zel \u00f6rnek, de\u011ferleri saate g\u00f6re Saat ad\u0131 verilen bir s\u00fctunda grupland\u0131r\u0131r ve ard\u0131ndan her saat i\u00e7in Sat\u0131\u015f […]<\/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-4055","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n library<\/span> (dplyr)\nlibrary<\/span> (lubridate)\n\n#group by hours in time column and calculate sum of sales\n<\/span>df %>%\n group_by(time=floor_date(time, ' 1 hour<\/span> ')) %>%\n summarize(sum_sales=sum(sales))\n<\/strong><\/pre>\n \u00d6rnek: verileri R’de zamana g\u00f6re grupland\u0131rma<\/strong><\/span><\/h2>\n
#create data frame\n<\/span>df <- data. frame<\/span> (time=as. POSIXct<\/span> (c('2022-01-01 01:14:00', '2022-01-01 01:24:15',\n '2022-01-01 02:52:19', '2022-01-01 02:54:00',\n '2022-01-01 04:05:10', '2022-01-01 05:35:09')),\n sales=c(18, 20, 15, 14, 10, 9))\n\n#view data frame\n<\/span>df\n\n time sales\n1 2022-01-01 01:14:00 18\n2 2022-01-01 01:24:15 20\n3 2022-01-01 02:52:19 15\n4 2022-01-01 02:54:00 14\n5 2022-01-01 04:05:10 10\n6 2022-01-01 05:35:09 9\n<\/span><\/span><\/strong><\/pre>\n library<\/span> (dplyr)\nlibrary<\/span> (lubridate)\n\n#group by hours in time column and calculate sum of sales\n<\/span>df %>%\n group_by(time=floor_date(time, ' 1 hour<\/span> ')) %>%\n summarize(sum_sales=sum(sales))\n\n`summarise()` ungrouping output (override with `.groups` argument)\n# A tibble: 4 x 2\n time sum_sales\n \n1 2022-01-01 01:00:00 38\n2 2022-01-01 02:00:00 29\n3 2022-01-01 04:00:00 10\n4 2022-01-01 05:00:00 9\n<\/strong><\/pre>\n\n
library<\/span> (dplyr)\nlibrary<\/span> (lubridate)\n\n#group by hours in time column and calculate mean of sales\n<\/span>df %>%\n group_by(time=floor_date(time, ' 1 hour<\/span> ')) %>%\n summarize(mean_sales=mean(sales))\n\n`summarise()` ungrouping output (override with `.groups` argument)\n# A tibble: 4 x 2\n time mean_sales\n \n1 2022-01-01 01:00:00 19 \n2 2022-01-01 02:00:00 14.5\n3 2022-01-01 04:00:00 10 \n4 2022-01-01 05:00:00 9<\/strong><\/pre>\n\n
Ek kaynaklar<\/strong><\/span><\/h2>\n
R’de veriler haftaya g\u00f6re nas\u0131l gruplan\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"