Global Temperatures

Dataset from week 20 of Andy Cotgreave and Andy Kriebel’s #Makeovermonday challenge

library(stringr)
library(dplyr)
library(ggplot2)

#Download file from onedrive if needed
if(!file.exists("temperatures.txt")){
  download.file("https://onedrive.live.com/download.aspx?cid=43EBDBC5D5265516&authKey=%21AH1yAX86LpyUja4&resid=43EBDBC5D5265516%2110356&ithint=%2Etxt","temperatures.txt")
}

#Load text file
temperatures.raw <- read.csv("temperatures.txt", sep = "\t", stringsAsFactors = FALSE)

#Create named month and numeric year columns
temperatures.dates <- as.data.frame(str_split_fixed(temperatures.raw$Year,"/",2))

temperatures.dates <- temperatures.dates %>%
  rename(year_num = V1,
         month_num = V2) %>%
  mutate(month_name = month.name[month_num],
         year_num = as.numeric(year_num))

temperatures <- cbind(temperatures.raw, temperatures.dates)

#Sort months
temperatures$month_name <- factor(temperatures$month_name, levels = month.name)

#Plot Data
ggplot(data=temperatures, aes(x=year_num, y=Median, colour=Median)) +
  geom_line() +
  scale_colour_gradient(low="yellow", high="Red") +
  facet_wrap(~ month_name) +
  theme(axis.title = element_blank(),
        axis.ticks = element_blank(),
        axis.text = element_blank())