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 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Arch Linux
## 
## Matrix products: default
## BLAS:   /usr/lib/libblas.so.3.10.1
## LAPACK: /usr/lib/liblapack.so.3.10.1
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] scatterpie_0.1.8 ggplot2_3.3.6   
## 
## loaded via a namespace (and not attached):
##  [1] prettydoc_0.4.1  tidyselect_1.1.2 xfun_0.31        bslib_0.4.0     
##  [5] purrr_0.3.4      ggfun_0.0.6      colorspace_2.0-3 vctrs_0.4.1     
##  [9] generics_0.1.3   htmltools_0.5.3  yaml_2.3.5       utf8_1.2.2      
## [13] rlang_1.0.4      jquerylib_0.1.4  pillar_1.8.0     glue_1.6.2      
## [17] withr_2.5.0      DBI_1.1.3        tweenr_1.0.2     lifecycle_1.0.1 
## [21] stringr_1.4.0    munsell_0.5.0    gtable_0.3.0     evaluate_0.15   
## [25] labeling_0.4.2   knitr_1.39       fastmap_1.1.0    fansi_1.0.3     
## [29] highr_0.9        Rcpp_1.0.9       scales_1.2.0     cachem_1.0.6    
## [33] jsonlite_1.8.0   farver_2.1.1     ggforce_0.3.3    digest_0.6.29   
## [37] stringi_1.7.8    dplyr_1.0.9      polyclip_1.10-0  grid_4.2.1      
## [41] cli_3.3.0.9000   tools_4.2.1      magrittr_2.0.3   sass_0.4.2      
## [45] maps_3.4.0       tibble_3.1.8     tidyr_1.2.0      pkgconfig_2.0.3 
## [49] MASS_7.3-58.1    ellipsis_0.3.2   assertthat_0.2.1 rmarkdown_2.14  
## [53] R6_2.5.1         compiler_4.2.1