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 4.3.0 (2023-04-21 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## 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_0.2.1 ggplot2_3.4.2   
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.3     jsonlite_1.8.4   highr_0.10       dplyr_1.1.2     
##  [5] compiler_4.3.0   maps_3.4.1       tidyselect_1.2.0 Rcpp_1.0.10     
##  [9] tidyr_1.3.0      ggfun_0.0.9      jquerylib_0.1.4  scales_1.2.1    
## [13] yaml_2.3.7       fastmap_1.1.1    R6_2.5.1         labeling_0.4.2  
## [17] generics_0.1.3   knitr_1.43       MASS_7.3-60      polyclip_1.10-4 
## [21] tibble_3.2.1     munsell_0.5.0    bslib_0.4.2      pillar_1.9.0    
## [25] rlang_1.1.1      utf8_1.2.3       cachem_1.0.7     xfun_0.39       
## [29] sass_0.4.6       cli_3.6.1        withr_2.5.0      magrittr_2.0.3  
## [33] tweenr_2.0.2     digest_0.6.31    grid_4.3.0       ggforce_0.4.1   
## [37] lifecycle_1.0.3  vctrs_0.6.2      evaluate_0.21    glue_1.6.2      
## [41] farver_2.1.1     prettydoc_0.4.1  fansi_1.0.4      colorspace_2.1-0
## [45] purrr_1.0.1      rmarkdown_2.21   tools_4.3.0      pkgconfig_2.0.3 
## [49] htmltools_0.5.5