library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Arnegg <- sunrise.set(47.4138069,9.257916799999975, "2023/01/01", timezone="MET", num.days=370) sunrise <- Arnegg$sunrise sunset <- Arnegg$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Arnegg["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Arnegg["ss"] <- as.POSIXct(sunset, format = "%H:%M") Arnegg["timestamp"] <- align.time(Arnegg$sunrise, 60*10) Arnegg <- Arnegg[c("timestamp", "sr", "ss")] locsrss <- ggplot(Arnegg, aes(x=Arnegg$timestamp)) + geom_line(aes(y=Arnegg$sr)) + geom_line(aes(y=Arnegg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Arnegg 2023", x = "Datum", y = "Zeit") pdf("Arnegg_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Arnegg_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Arnegg["Sonnenaufgang"] <- strftime(Arnegg$sr, format="%H:%M") Arnegg["Sonnenuntergang"] <- strftime(Arnegg$ss, format="%H:%M") write.table(Arnegg, file="Arnegg_SaSu.csv", dec=',', sep=';', row.names=FALSE)