Heatmap of world Temperature in r package for ggplot2

WorldHeat.r

### FORKED FROM: https://gist.github.com/cavedave/8ff22e94c882e9f6be933f99f2ae0b50
## Charles changed:
##   Absolute URLs to library/data (rather than local files)
##   Raster rather than tiles (didn't like the grid lines)
##   Gradient from red (hot) to blue (cold) with black at zero (no change from average)
##   Removed year filter
##   Defined title and breaks via automatic extraction of dates from data
##   Scaled down plot to be more friendly for Gist
##   Took out unused libraries

## install.packages(c("dplyr", "tidyr", "ggplot2", "ggthemes"))

#This is inspired by this piral animation of the same dataset
#http://www.climate-lab-book.ac.uk/2016/spiralling-global-temperatures/
#and this R code to produce the animation
#https://gist.github.com/jebyrnes/b34930da0052a86f5ffe254ce9900357
# It also uses elements of this http://www.r-bloggers.com/making-faceted-heatmaps-with-ggplot2/ 
# and this https://rpubs.com/bradleyboehmke/weather_graphic graphic

library(dplyr)
library(tidyr)
library(ggplot2)
library(ggthemes)
#Data explanation at https://crudata.uea.ac.uk/cru/data/temperature/
#r code to read data https://crudata.uea.ac.uk/cru/data/temperature/read_cru_hemi.r
# data https://crudata.uea.ac.uk/cru/data/temperature/HadCRUT4-gl.dat
#As well as data read in script
source("https://crudata.uea.ac.uk/cru/data/temperature/read_cru_hemi.r")
temp_dat <- read_cru_hemi("https://crudata.uea.ac.uk/cru/data/temperature/HadCRUT4-gl.dat")

#remove cover
temp_dat_monthly <- temp_dat %>%
  select(-starts_with("cover")) %>%
  select(-starts_with("annual")) %>%
  gather(month, anomaly, -year) %>%
  mutate(month = gsub("month\\.", "", month)) %>%
  mutate(month = as.numeric(month)) 

dgr_fmt <- function(x, ...) {
        parse(text = paste(x, "", sep = ""))
}

months <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")
minYr  <- min(temp_dat_monthly$year)
maxYr  <- max(temp_dat_monthly$year)
maxMon <- max(temp_dat_monthly[temp_dat_monthly$year == maxYr &
                               !is.na(temp_dat_monthly$anomaly), "month"] )
brk <- seq(minYr, maxYr, by=10)

gg <- ggplot(temp_dat_monthly, aes(x=month, y=year, fill=anomaly))
gg <- gg + geom_raster()
gg <- gg + scale_fill_gradient2(name="Difference from \nAverage in °C", na.value="white",
                                mid="black", midpoint=0, low="blue", high="red")
plot.title = paste('Average World Temperature from', minYr,
                   'to', months[ maxMon ], maxYr)
plot.subtitle = 'Data is HadCRUT4-gl from crudata'
gg <- gg + ggtitle(bquote(atop(.(plot.title), atop(italic(.(plot.subtitle)), ""))))
gg <- gg + labs(x=NULL, y=NULL)


gg <- gg + theme_tufte(base_family="Helvetica")
gg <- gg +
        coord_cartesian(ylim = c(1850,2015)) +
        scale_y_continuous(breaks = brk, labels = brk) +
        scale_x_continuous(expand = c(0, 0), 
                           breaks = c(1,2,3,4,5,6,7,8,9,10,11,12),
                           labels = months)

gg <- gg + theme(plot.title=element_text(hjust=0))
gg <- gg + theme(axis.ticks=element_blank())
gg <- gg + theme(axis.text=element_text(size=7))
ggsave("heat.png", width=5, height=3, dpi=150)
print(gg)