library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Freilassing <- sunrise.set(47.8419982,12.9728226, "2019/01/01", timezone="MET", num.days=370) sunrise <- Freilassing$sunrise sunset <- Freilassing$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Freilassing["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Freilassing["ss"] <- as.POSIXct(sunset, format = "%H:%M") Freilassing["timestamp"] <- align.time(Freilassing$sunrise, 60*10) Freilassing <- Freilassing[c("timestamp", "sr", "ss")] locsrss <- ggplot(Freilassing, aes(x=Freilassing$timestamp)) + geom_line(aes(y=Freilassing$sr)) + geom_line(aes(y=Freilassing$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Freilassing 2019", x = "Datum", y = "Zeit") pdf("Freilassing_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Freilassing_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Freilassing["Sonnenaufgang"] <- strftime(Freilassing$sr, format="%H:%M") Freilassing["Sonnenuntergang"] <- strftime(Freilassing$ss, format="%H:%M") write.table(Freilassing, file="Freilassing_SaSu.csv", dec=',', sep=';', row.names=FALSE)