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 4.4.1 (2024-06-14 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 22621)
## 
## Matrix products: default
## 
## 
## 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_0.2.4 ggplot2_3.5.1   
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.5          jsonlite_1.8.8        highr_0.11           
##  [4] dplyr_1.1.4           compiler_4.4.1        maps_3.4.2           
##  [7] tidyselect_1.2.1      Rcpp_1.0.13           tidyr_1.3.1          
## [10] ggfun_0.1.5.001       jquerylib_0.1.4       scales_1.3.0         
## [13] yaml_2.3.10           fastmap_1.2.0         R6_2.5.1             
## [16] labeling_0.4.3        generics_0.1.3        knitr_1.48           
## [19] yulab.utils_0.1.7.001 MASS_7.3-61           polyclip_1.10-7      
## [22] tibble_3.2.1          munsell_0.5.1         bslib_0.8.0          
## [25] pillar_1.9.0          rlang_1.1.4           utf8_1.2.4           
## [28] cachem_1.1.0          xfun_0.46             fs_1.6.4             
## [31] sass_0.4.9            cli_3.6.3             withr_3.0.1          
## [34] magrittr_2.0.3        tweenr_2.0.3          digest_0.6.36        
## [37] grid_4.4.1            ggforce_0.4.2         lifecycle_1.0.4      
## [40] vctrs_0.6.5           evaluate_0.24.0       glue_1.7.0           
## [43] farver_2.1.2          prettydoc_0.4.1       fansi_1.0.6          
## [46] colorspace_2.1-1      purrr_1.0.2           rmarkdown_2.27       
## [49] tools_4.4.1           pkgconfig_2.0.3       htmltools_0.5.8.1