動機

一つのプロットにおける複数のデータについて、別々のカラースケールを使いたい時。

Load packages

library(magrittr)
library(ggplot2)

ダメな例

irisのSepal (萼片) とPetal (花弁) を同じ一つの散布図にそれぞれ分けて作図することを考える。どちらもSpeciesで色分けしたいが、SepalとPetalで色分けを変えたい場合どうするか？

以下のように、それぞれの散布図(geom_point)の下に、そのままそれぞれの色を指定する(scale_color_viridis_d)と、古い色の指定は新しいカラースケールに上書きされて、 Sepal、Petal両方に同じカラースケールが適用される。

Code

theme_scatter <- function() {
  list(
    theme_void(base_size = 14),
    theme(
      panel.background = element_rect(fill = "grey80")
    )
  )
}

(gp1 <-
   iris %>%
   ggplot(aes(Sepal.Length, Sepal.Width)) +
   geom_point(aes(color = Species), size = 2) +
   scale_color_viridis_d(option = "A", begin = .1, end = .5) +
   geom_point(
     aes(Petal.Length, Petal.Width, color = Species),
     shape = 2, size = 2
   ) +
   scale_color_viridis_d(option = "D", begin = .1, end = .5) +
   theme_scatter())

Scale for colour is already present.
Adding another scale for colour, which will replace the existing scale.

`ggnewscale`パッケージを使う

ggnewscale::new_scale_color()を各スケールの間に挟むと、別のscale_color_*()が利用できる。

(gp2 <-
   iris %>%
   ggplot(aes(Sepal.Length, Sepal.Width)) +
   geom_point(aes(color = Species), size = 2) +
   scale_color_viridis_d(option = "A", begin = .1, end = .5) +
   ggnewscale::new_scale_color() +
   geom_point(
     aes(Petal.Length, Petal.Width, color = Species),
     shape = 2, size = 2
   ) +
   scale_color_viridis_d(option = "D", begin = .1, end = .5) +
   theme_scatter())

凡例を分ける

凡例を別々にコントロールしたい時は、scale_color_*()のguide引数にguide_*()を渡す。

(gp3 <-
   iris %>%
   ggplot(aes(Sepal.Length, Sepal.Width)) +
   geom_point(aes(color = Species), size = 2) +
   scale_color_viridis_d(option = "A", begin = .1, end = .5) +
   ggnewscale::new_scale_color() +
   geom_point(
     aes(Petal.Length, Petal.Width, color = Species),
     shape = 2, size = 2
   ) +
   scale_color_viridis_d(option = "D", begin = .1, end = .5,
                         guide = guide_legend(title = "new")) +
   theme_scatter())

facetでも分けて、色も分ける場合

描画するデータをdplyr::filter()で分けて、複数回プロットすればよい。

tbl_plot <-
  iris %>%
  tibble::as_tibble() %>%
  dplyr::mutate(rn = dplyr::row_number()) %>%
  tidyr::pivot_longer(cols = !c(Species, rn)) %>%
  dplyr::mutate(
    part = stringr::str_extract(name, "^[^.]+"),
    measure = stringr::str_extract(name, "[^.]+$"),
  ) %>%
  dplyr::select(!name) %>%
  tidyr::pivot_wider(names_from = measure, values_from = value)
tbl_plot

# A tibble: 300 × 5
   Species    rn part  Length Width
   <fct>   <int> <chr>  <dbl> <dbl>
 1 setosa      1 Sepal    5.1   3.5
 2 setosa      1 Petal    1.4   0.2
 3 setosa      2 Sepal    4.9   3  
 4 setosa      2 Petal    1.4   0.2
 5 setosa      3 Sepal    4.7   3.2
 6 setosa      3 Petal    1.3   0.2
 7 setosa      4 Sepal    4.6   3.1
 8 setosa      4 Petal    1.5   0.2
 9 setosa      5 Sepal    5     3.6
10 setosa      5 Petal    1.4   0.2
# ℹ 290 more rows

tbl_plot %>%
  ggplot(aes(Length, Width, shape = part)) +
  geom_point(data = \(df) dplyr::filter(df, part == "Petal"), aes(color = Species)) +
  ggnewscale::new_scale_color() +
  geom_point(data = \(df) dplyr::filter(df, part == "Sepal"), aes(color = Species)) +
  scale_color_viridis_d(option = "B", guide = guide_legend(title = "Species for Sepal")) +
  facet_wrap(~ part, scales = "free") +
  theme_scatter()

`ggnewscale::new_scale_color()`は何回も使える

plot_facet <- function(temp_facet, temp_option) {
  list(
    geom_point(data = \(df) dplyr::filter(df, facet == temp_facet), aes(color = Species)),
    scale_color_viridis_d(begin = .1, end = .9, option = temp_option, guide = guide_legend(title = temp_option))
  )
}

purrr::map(1:6, ~ dplyr::mutate(dplyr::slice_head(iris, n = 10, by = Species), facet = .x)) %>%
  dplyr::bind_rows() %>%
  ggplot(aes(Sepal.Length, Sepal.Width)) +
  plot_facet(1, "A") +
  ggnewscale::new_scale_colour() +
  plot_facet(2, "B") +
  ggnewscale::new_scale_colour() +
  plot_facet(3, "C") +
  ggnewscale::new_scale_colour() +
  plot_facet(4, "D") +
  ggnewscale::new_scale_colour() +
  plot_facet(5, "E") +
  ggnewscale::new_scale_colour() +
  plot_facet(6, "F") +
  facet_wrap(~ facet) +
  theme_scatter() +
  theme(legend.direction = "horizontal",
        legend.margin = margin(),
        legend.spacing.y = unit(2, "mm"))

Session info

sessionInfo()

R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Asia/Tokyo
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_3.5.1  magrittr_2.0.3

loaded via a namespace (and not attached):
 [1] vctrs_0.6.5       cli_3.6.3         knitr_1.48        rlang_1.1.4      
 [5] xfun_0.46         stringi_1.8.4     purrr_1.0.2       generics_0.1.3   
 [9] jsonlite_1.8.8    labeling_0.4.3    glue_1.7.0        colorspace_2.1-1 
[13] htmltools_0.5.7   scales_1.3.0      fansi_1.0.6       rmarkdown_2.25   
[17] grid_4.3.2        evaluate_0.24.0   munsell_0.5.1     tibble_3.2.1     
[21] fastmap_1.1.1     yaml_2.3.9        lifecycle_1.0.4   stringr_1.5.1    
[25] compiler_4.3.2    dplyr_1.1.4       htmlwidgets_1.6.4 pkgconfig_2.0.3  
[29] tidyr_1.3.1       farver_2.1.2      digest_0.6.34     viridisLite_0.4.2
[33] R6_2.5.1          tidyselect_1.2.1  utf8_1.2.4        pillar_1.9.0     
[37] withr_3.0.0       tools_4.3.2       gtable_0.3.5      ggnewscale_0.5.0

動機