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 4.0.5 (2021-03-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Arch Linux
## 
## Matrix products: default
## BLAS:   /usr/lib/libblas.so.3.9.0
## LAPACK: /usr/lib/liblapack.so.3.9.0
## 
## 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_0.1.6 ggplot2_3.3.3   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.6          highr_0.9           BiocManager_1.30.12
##  [4] bslib_0.2.4         compiler_4.0.5      pillar_1.6.0       
##  [7] jquerylib_0.1.3     prettydoc_0.4.1     tools_4.0.5        
## [10] digest_0.6.27       jsonlite_1.7.2      evaluate_0.14      
## [13] lifecycle_1.0.0     tibble_3.1.1        gtable_0.3.0       
## [16] pkgconfig_2.0.3     rlang_0.4.10        DBI_1.1.1          
## [19] rvcheck_0.1.8       yaml_2.2.1          xfun_0.22          
## [22] withr_2.4.2         stringr_1.4.0       dplyr_1.0.5        
## [25] knitr_1.32          maps_3.3.0          generics_0.1.0     
## [28] sass_0.3.1          vctrs_0.3.7         grid_4.0.5         
## [31] tidyselect_1.1.0    glue_1.4.2          R6_2.5.0           
## [34] fansi_0.4.2         rmarkdown_2.7       polyclip_1.10-0    
## [37] tidyr_1.1.3         farver_2.1.0        tweenr_1.0.2       
## [40] purrr_0.3.4         magrittr_2.0.1      MASS_7.3-53.1      
## [43] scales_1.1.1        htmltools_0.5.1.1   ellipsis_0.3.1     
## [46] assertthat_0.2.1    ggforce_0.3.3       colorspace_2.0-0   
## [49] labeling_0.4.2      utf8_1.2.1          stringi_1.5.3      
## [52] munsell_0.5.0       crayon_1.4.1