library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Davensberg <- sunrise.set(51.8175172,7.595306100000016, "2022/01/01", timezone="MET", num.days=370) sunrise <- Davensberg$sunrise sunset <- Davensberg$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Davensberg["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Davensberg["ss"] <- as.POSIXct(sunset, format = "%H:%M") Davensberg["timestamp"] <- align.time(Davensberg$sunrise, 60*10) Davensberg <- Davensberg[c("timestamp", "sr", "ss")] locsrss <- ggplot(Davensberg, aes(x=Davensberg$timestamp)) + geom_line(aes(y=Davensberg$sr)) + geom_line(aes(y=Davensberg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Davensberg 2022", x = "Datum", y = "Zeit") pdf("Davensberg_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Davensberg_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Davensberg["Sonnenaufgang"] <- strftime(Davensberg$sr, format="%H:%M") Davensberg["Sonnenuntergang"] <- strftime(Davensberg$ss, format="%H:%M") write.table(Davensberg, file="Davensberg_SaSu.csv", dec=',', sep=';', row.names=FALSE)