1 安装

patchwork

devtools::install_github("thomasp85/patchwork")

2 使用

拼图有两种不同的含义:

1. 像一幅图中不同的panel一样,他们分别是独立的;

2. 反映同样的数据信息,将几个图拼成一个panel.比如对于一个散点图,在其右侧和左侧分别添加其对应的变量的密度分布图等.

library(patchwork)
library(tidyverse)

## Warning: package 'tidyverse' was built under R version 3.6.1

## -- Attaching packages -------------------------------------------------------------------------------------------- tidyverse 1.2.1 --

## v ggplot2 3.2.1     v purrr   0.3.2
## v tibble  2.1.3     v dplyr   0.8.3
## v tidyr   1.0.0     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.4.0

## Warning: package 'ggplot2' was built under R version 3.6.1

## Warning: package 'tibble' was built under R version 3.6.1

## Warning: package 'tidyr' was built under R version 3.6.1

## Warning: package 'dplyr' was built under R version 3.6.1

## -- Conflicts ----------------------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

plot1 <- 
  ggplot(mtcars, aes(x = mpg, y = disp)) +
  geom_point() +
  theme_bw() +
  scale_x_continuous(limits = c(10, 35)) +
  scale_y_continuous(limits = c(50, 500))
  
plot2 <- 
  ggplot(mtcars, aes(x = mpg)) +
  geom_histogram() +
  theme_bw() +
  scale_x_continuous(limits = c(10, 35), 
                     name = NULL, labels = NULL, breaks = NULL) +
  scale_y_continuous(expand = expand_scale(mult = c(0, .05))) +
  theme(panel.border = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())

plot3 <- 
  ggplot(mtcars, aes(x = disp)) +
  geom_histogram() +
  theme_bw() +
  coord_flip() +
    scale_x_continuous(limits = c(150, 500), 
                     name = NULL, labels = NULL, breaks = NULL) +
  scale_y_continuous(expand = expand_scale(mult = c(0, .05))) +
  theme(panel.border = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())

我们画出了汽车mpg和disp的关系,然后想在这个散点图上方和右方分别画上disp和mpg的分布图.这时候需要注意的是,需要确定xlim和ylim的发明,从而使其坐标轴能够精确对上.

plot <- 
{plot2 + plot_spacer() + plot_layout(ncol = 2, widths = c(3, 1))} -
  {plot1 + plot3 + plot_layout(ncol = 2, widths = c(3, 1))} +
  plot_layout(ncol = 1, heights = c(1,3))
plot

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## Warning: Removed 2 rows containing missing values (geom_bar).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## Warning: Removed 12 rows containing non-finite values (stat_bin).

## Warning: Removed 2 rows containing missing values (geom_bar).

plot_spacer()函数用来生成一个空白图片.plot_layout()函数用来设置拼接图片的一些具体参数,如列数,行数,宽度或者高度比等.

{}括起来的几个plot组成一个完整的新的plot.

这里面需要注意的是-.它是指该符号左右两侧当成两个新的图层进行拼接.

具体使用方法可以参考作者github(https://github.com/thomasp85/patchwork).