Scatter Pie plot

set.seed(123)
long <- rnorm(50, sd=100)
lat <- rnorm(50, sd=50)
d <- data.frame(long=long, lat=lat)
d <- with(d, d[abs(long) < 150 & abs(lat) < 70,])
n <- nrow(d)
d$region <- factor(1:n)
d$A <- abs(rnorm(n, sd=1))
d$B <- abs(rnorm(n, sd=2))
d$C <- abs(rnorm(n, sd=3))
d$D <- abs(rnorm(n, sd=4))
d[1, 4:7] <- d[1, 4:7] * 3
head(d)
##          long        lat region          A        B        C        D
## 1  -56.047565  12.665926      1 2.13121969 8.663359 3.928711 8.676792
## 2  -23.017749  -1.427338      2 0.25688371 1.403569 1.375096 4.945092
## 4    7.050839  68.430114      3 0.24669188 0.524395 3.189978 5.138863
## 5   12.928774 -11.288549      4 0.34754260 3.144288 3.789556 2.295894
## 8 -126.506123  29.230687      5 0.95161857 3.029335 1.048951 2.471943
## 9  -68.685285   6.192712      6 0.04502772 3.203072 2.596539 4.439393
ggplot() + geom_scatterpie(aes(x=long, y=lat, group=region), data=d,
                           cols=LETTERS[1:4]) + coord_equal()

d$radius <- 6 * abs(rnorm(n))
p <- ggplot() + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius), data=d,
                                cols=LETTERS[1:4], color=NA) + coord_equal()
p + geom_scatterpie_legend(d$radius, x=-140, y=-70)

The geom_scatterpie is especially useful for visualizing data on a map.

world <- map_data('world')
p <- ggplot(world, aes(long, lat)) +
    geom_map(map=world, aes(map_id=region), fill=NA, color="black") +
    coord_quickmap()
p + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius),
                    data=d, cols=LETTERS[1:4], color=NA, alpha=.8) +
    geom_scatterpie_legend(d$radius, x=-160, y=-55)

p + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius),
                    data=d, cols=LETTERS[1:4], color=NA, alpha=.8) +
    geom_scatterpie_legend(d$radius, x=-160, y=-55, n=3, labeller=function(x) 1000*x^2)

Session info

Here is the output of sessionInfo() on the system on which this document was compiled:

## R version 3.5.0 (2018-04-23)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS High Sierra 10.13.4
## 
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] maps_3.3.0       scatterpie_0.1.2 ggplot2_3.0.0   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.17      pillar_1.3.0      compiler_3.5.0   
##  [4] plyr_1.8.4        bindr_0.1.1       prettydoc_0.2.1  
##  [7] tools_3.5.0       digest_0.6.15     evaluate_0.10.1  
## [10] tibble_1.4.2      gtable_0.2.0      pkgconfig_2.0.1  
## [13] rlang_0.2.1       rvcheck_0.1.0     yaml_2.1.19      
## [16] bindrcpp_0.2.2    withr_2.1.2       stringr_1.3.1    
## [19] dplyr_0.7.6       knitr_1.20        rprojroot_1.3-2  
## [22] grid_3.5.0        tidyselect_0.2.4  glue_1.2.0       
## [25] R6_2.2.2          rmarkdown_1.10    tidyr_0.8.1      
## [28] farver_1.0        purrr_0.2.5       tweenr_0.1.5.9999
## [31] magrittr_1.5      units_0.6-0       backports_1.1.2  
## [34] scales_0.5.0.9000 htmltools_0.3.6   MASS_7.3-50      
## [37] assertthat_0.2.0  ggforce_0.1.3     colorspace_1.3-2 
## [40] labeling_0.3      stringi_1.2.3     lazyeval_0.2.1   
## [43] munsell_0.5.0     crayon_1.3.4