library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Ankara <- sunrise.set(39.92448212528485,32.853240966796875, "2022/01/01", timezone="MET", num.days=370) sunrise <- Ankara$sunrise sunset <- Ankara$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Ankara["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Ankara["ss"] <- as.POSIXct(sunset, format = "%H:%M") Ankara["timestamp"] <- align.time(Ankara$sunrise, 60*10) Ankara <- Ankara[c("timestamp", "sr", "ss")] locsrss <- ggplot(Ankara, aes(x=Ankara$timestamp)) + geom_line(aes(y=Ankara$sr)) + geom_line(aes(y=Ankara$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Ankara 2022", x = "Datum", y = "Zeit") pdf("Ankara_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Ankara_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Ankara["Sonnenaufgang"] <- strftime(Ankara$sr, format="%H:%M") Ankara["Sonnenuntergang"] <- strftime(Ankara$ss, format="%H:%M") write.table(Ankara, file="Ankara_SaSu.csv", dec=',', sep=';', row.names=FALSE)