1

I caculated correlations between temperatures und the date of grape harvest. I stored the results as matrix:

       32.5         37.5        42.5       47.5          52.5        57.5        62.5
-12.5 -0.05783118 -0.001655467 -0.07857098 -0.1526494 -0.0007327898 -0.02078552  0.06121682
-7.5  -0.23219824 -0.059952117 -0.06895444 -0.1674386 -0.1311612338 -0.08476390  0.09831010
-2.5  -0.11040995 -0.147325160 -0.15016740 -0.1796807 -0.1819844495 -0.14472899 -0.03550576
2.5   -0.20577359 -0.180857373 -0.15077067 -0.2293366 -0.2577666092 -0.21645676 -0.13044584
7.5   -0.44526971 -0.176224708 -0.15114994 -0.2459971 -0.2741514139 -0.19281484 -0.15683870
12.5  -0.12481683 -0.121675085 -0.16011098 -0.2288839 -0.2503969467 -0.26616721 -0.23089796
17.5  -0.15352693 -0.220012419 -0.11456690 -0.2314059 -0.2194705426 -0.20557053 -0.22529422

Now I want to visualize the results on a map. It should look like this:

example for visualizing correlations on a map

Only my longitude und latitude are different. My latitude ranges from 32,5°N to 62,5°N and my longitude goes from -12,5°E to 17,5°E. I have absolutely no idea how it's been done! It would be nice, if someone can help me. Regards.

user3289994
  • 11
  • 3
  • First, convert your dataset, so that it has following columns: lon lat correlation. Then check if solutions mentioned in this question are applicable: http://stackoverflow.com/questions/7747991/geographical-heat-map-in-r – Nikita Barsukov Mar 13 '14 at 13:01

2 Answers2

1

This is one way. Your grid is rather coarse (increments of 5°, or ~350 miles at the equator), and of course you did not provide an actual map, but this will plot a "heat map" of correlation at the coordinates you provided.

df <- cbind(lon=rownames(df),df)
library(reshape2)
library(ggplot2)
library(RColorBrewer)
gg <- melt(df,id="lon",variable.name="lat",value.name="corr")
gg$lat <- as.numeric(substring(gg$lat,2))  # remove pre-pended "X"
gg$lon <- as.numeric(as.character(gg$lon)) # convert factor to numeric
ggplot(gg)+
  geom_tile(aes(x=lon,y=lat, fill=corr))+
  scale_fill_gradientn(colours=rev(brewer.pal(9,"Spectral")))+
  coord_fixed()

jlhoward
  • 58,004
  • 7
  • 97
  • 140
0

The corrplot() function from corrplot R package can be used to plot a correlogram. 

library(corrplot)  
M<-cor(mtcars) # compute correlation matrix
corrplot(M, method="circle")

this is described here:

Online R software is also available to compute and visualize a correlation matrix, by a simple click without any installation :

http://www.sthda.com/english/rsthda/correlation-matrix.php

A. Kassambara
  • 228
  • 1
  • 5