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 4.5.1 (2025-06-13 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 26100)
## 
## Matrix products: default
##   LAPACK version 3.12.1
## 
## locale:
## [1] LC_COLLATE=C                               
## [2] LC_CTYPE=Chinese (Simplified)_China.utf8   
## [3] LC_MONETARY=Chinese (Simplified)_China.utf8
## [4] LC_NUMERIC=C                               
## [5] LC_TIME=Chinese (Simplified)_China.utf8    
## 
## time zone: Asia/Shanghai
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] scatterpie_0.2.6 ggplot2_4.0.0   
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6          jsonlite_2.0.0        dplyr_1.1.4          
##  [4] compiler_4.5.1        maps_3.4.3            tidyselect_1.2.1     
##  [7] tidyr_1.3.1           jquerylib_0.1.4       ggfun_0.2.0.001      
## [10] scales_1.4.0          yaml_2.3.10           fastmap_1.2.0        
## [13] R6_2.6.1              labeling_0.4.3        generics_0.1.4       
## [16] knitr_1.50            yulab.utils_0.2.1.002 MASS_7.3-65          
## [19] polyclip_1.10-7       tibble_3.3.0          bslib_0.9.0          
## [22] pillar_1.11.0         RColorBrewer_1.1-3    rlang_1.1.6          
## [25] cachem_1.1.0          xfun_0.53             fs_1.6.6             
## [28] sass_0.4.10           S7_0.2.0              cli_3.6.5            
## [31] withr_3.0.2           magrittr_2.0.3        tweenr_2.0.3         
## [34] digest_0.6.37         grid_4.5.1            ggforce_0.5.0        
## [37] rappdirs_0.3.3        lifecycle_1.0.4       vctrs_0.6.5          
## [40] evaluate_1.0.5        glue_1.8.0            farver_2.1.2         
## [43] prettydoc_0.4.1       purrr_1.1.0           rmarkdown_2.29       
## [46] tools_4.5.1           pkgconfig_2.0.3       htmltools_0.5.8.1