library(tidyverse)
library(ggsci)

分面

mtcar_tbl = rownames_to_column(mtcars, var = 'car')%>%
  mutate(cyl = factor(cyl),
         am = if_else(am == 1, 'A', 'N'),
         vs = if_else(vs == 1, 'V', 'L'))

facet_grid 双变量分面,把am和vs信息也放进图里

ggplot(mtcar_tbl,aes(x= wt,y = mpg))+
  geom_point(shape = 21,
             alpha = 0.5,
             aes(size = disp, fill = factor(cyl)))+
  scale_fill_npg()+
  scale_size(range = c(1,20))+
  facet_grid(vs~am, scales = 'free_x') +#允许自由适应x坐标
  theme_bw()

仅需要通过单变量分面，但面数又太多了的时候:

small_diamonds = sample_n(diamonds, 500)
ggplot(data = small_diamonds,aes(x = carat, y =price))+
  geom_point(shape = 21,size = 2,
             color = 'black', aes(fill = cut))+
  scale_fill_npg()+
  facet_wrap(~color, nrow = 2)+
  theme_bw()+
  theme(legend.position = c(0.9,0.3))

来自不同变量的分面

library(ggforce)

ggplot(data = mtcar_tbl, aes(x = .panel_x, y = .panel_y))+
  geom_point(shape = 21,
             aes(fill = factor(cyl)))+
  scale_fill_npg()+
  facet_matrix(rows = vars(disp,wt),cols = vars(mpg,qsec))+
  theme_bw()

局部放大

library(ggforce)

ggplot(data = iris, aes(x = Petal.Length, y = Petal.Width,
                        color = Species))+
  geom_point(size = 3)+
  scale_fill_npg()+
  facet_zoom(x= Species == 'versicolor',##设置需要放大的条件
             zoom.size = 1)+#调整放大倍数
  theme_test()

加标记

ggplot(data = iris, aes(x = Petal.Length, y = Petal.Width,
                        color = Species))+
  geom_point(size = 3)+
  geom_mark_ellipse(aes(label = Species))+##加标记和椭圆
  scale_fill_lancet()+
  theme_test()+
  theme(legend.position = 'none')#去掉旁边的标注

添加子表/图

iris_stat = group_by(iris,Species)%>%
  summarise(Petal.Length = mean(Petal.Length),
            Petal.Width = mean(Petal.Width))

p0 = ggplot(data = iris, aes(x = Species, y = Sepal.Length))+
  geom_boxplot(aes(fill = Species), outlier.shape = 21)+
  scale_fill_lancet()+
  theme_classic()+
  theme(legend.position = 'none',
        axis.title.x = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        plot.background = element_blank())

位置表

tbl_pos = tibble(x= 7, y = 0.2, tb = list(iris_stat))
plot_pos = tibble(x = 7, y = 0, plot = list(p0))

library(ggpmisc)
ggplot(data = iris, aes(x = Petal.Length, y = Petal.Width,
                        color = Species))+
  geom_point(size = 3)+
  geom_table(data = tbl_pos,aes(x = x, y=y ,label = tb))+
  scale_fill_npg()+
  theme_test()+
  theme(legend.position = c(0.1,0.8))

添加子图

ggplot(data = iris, aes(x = Petal.Length, y = Petal.Width,
                        color = Species))+
  geom_point(size = 3)+
  geom_plot(data = plot_pos,aes(x = x, y=y ,label = plot))+
  scale_fill_npg()+
  theme_test()+
  theme(legend.position = c(0.1,0.8)) 

拼图

library(patchwork)
p1 = ggplot(mtcars)+
  geom_point(aes(mpg,disp,color = factor(cyl))) +
  ggtitle( 'Plot 1')

p2 = ggplot(mtcars)+
  geom_boxplot(aes(gear,disp,group = gear, fill = factor(gear))) +
  ggtitle( 'Plot 2')

p3 = ggplot(mtcars)+
  geom_point(aes(hp,wt,color = factor(cyl))) +
  ggtitle('Plot 3')

p4 = ggplot(mtcars)+
  geom_bar(aes(gear)) +
  facet_wrap(~cyl)+
  ggtitle( 'Plot 4')

p1+p2
p1/p2
p1/((p2/p3)|p4)

p1在最上层，其他的在下层。其中p2和p3也存在分层，但p4和这个整体并列

p1/(p2+p3)/p4 + plot_layout(heights = c(1,2,1),widths = c(2,1))+#设置图形的宽高比例
  plot_annotation(title = 'The plots',
                  tag_levels = 'A')&#可以直接指定所有图的标签
  theme_bw()

前面用&才可以修改所有图的theme

图例收集

可以通过修改guide_area()的位置来改图例的位置

p1+p3+guide_area()+plot_layout(guides = 'collect')