library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Egeln <- sunrise.set(51.9411082,11.4281059, "2022/01/01", timezone="MET", num.days=370) sunrise <- Egeln$sunrise sunset <- Egeln$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Egeln["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Egeln["ss"] <- as.POSIXct(sunset, format = "%H:%M") Egeln["timestamp"] <- align.time(Egeln$sunrise, 60*10) Egeln <- Egeln[c("timestamp", "sr", "ss")] locsrss <- ggplot(Egeln, aes(x=Egeln$timestamp)) + geom_line(aes(y=Egeln$sr)) + geom_line(aes(y=Egeln$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Egeln 2022", x = "Datum", y = "Zeit") pdf("Egeln_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Egeln_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Egeln["Sonnenaufgang"] <- strftime(Egeln$sr, format="%H:%M") Egeln["Sonnenuntergang"] <- strftime(Egeln$ss, format="%H:%M") write.table(Egeln, file="Egeln_SaSu.csv", dec=',', sep=';', row.names=FALSE)