Difference between revisions of "Outdoor air temperature in Finland"

library(OpasnetUtils)
library(ggplot2)
objects.latest("Op_en2959", code_name = "temperatures")

ggplot(subset(temperdays@data, Time %in% c("2013", "2030", "2050")), aes(x = Temperature, y = Result, color = Time, group = Time))+geom_line()

## This is code is Op_en2959/temperatures [[Outdoor air temperature in Finland]]
library(OpasnetUtils)

ta <- opbase.data("Op_en2959", subset = "Vantaa") # [[Outdoor air temperature in Finland]]
levels(ta$Year)[as.numeric(as.character(levels(ta$Year))) < 2015] <- "2012"
ta$Date <- as.POSIXct(paste(ta$Year, ta$Month, ta$Day, sep = "-"))

days <- aggregate(ta[c(
	"Temperature" # We only need temperature, but it is easy to take any other variable as well.
#	"Relative_humidity",
#	"Wind_direction",
#	"Wind_speed",
#	"Direct_normal_solar_radiation",
#	"Diffuse_horisontal_radiation",
#	"Result" # Global_horizontal_radiation
)], ta[c("Date", "Year")], FUN = mean)
colnames(days)[colnames(days) == "Temperature"] <- "Result"
days$Temperature <- cut(days$Result, breaks = seq(-30, 33, 3))
temperatures <- Ovariable("temperatures", data = aggregate(days["Result"], days[c("Temperature", "Year")], FUN = mean))
temperdays <- Ovariable("temperdays", data = aggregate(days["Result"], days[c("Temperature", "Year")], FUN = length))

years = data.frame(Time = 1985:2070, Year = c(rep("2012", 36), rep("2030", 20), rep("2050", 30)))

temperatures@data <- merge(temperatures@data, years)
temperatures@data$Year <- NULL
temperdays@data <- merge(temperdays@data, years)
temperdays@data$Year <- NULL

objects.store(temperatures, temperdays)
cat("Objects temperatures, temperdays stored.\n")

#ggplot(hours, aes(x = Time, y = Result))+geom_line() + geom_point(data = days, aes(x = Date, y = Result, colour = "Daily mean", size = 2))
#ggplot(hours, aes(x = Time, y = Result))+geom_point()