ggplot2使用技巧

R Graphics Cookbook, 2nd edition

https://r-graphics.org/

ggplot2高效实用指南 - 生信宝典

https://mp.weixin.qq.com/s/v3qtAgIMpo6vxxHUjlFagQ

ggplot2实用教程精选 - YuLabSMU

https://mp.weixin.qq.com/s/8dZA2HkrBytuvlSepQ1Ucw

Use R package export to export Rplots to PPT

export is an R package to easily export active R graphs and statistical output in publication quality to Microsoft Office, HTML, and Latex. More information on GitHub.

Get the latest development version from GitHub

install.packages("officer")
install.packages("rvg")
install.packages("openxlsx")
install.packages("ggplot2")
install.packages("flextable")
install.packages("xtable")
install.packages("rgl")
install.packages("stargazer")
install.packages("tikzDevice")
install.packages("xml2")
install.packages("broom")
install.packages("devtools")

devtools::install_github("tomwenseleers/export")

Getting Started

library(export)
      
?graph2ppt
?graph2doc
?graph2svg
?graph2png
?table2ppt
?table2tex
?table2excel
?table2doc
?table2html

## export of ggplot2 plot
library(ggplot2)
qplot(Sepal.Length, Petal.Length, data = iris, color = Species, size = Petal.Width, alpha = I(0.7))
# export to Powerpoint      
graph2ppt()      
graph2ppt(file="ggplot2_plot.pptx", aspectr=1.7)
# add 2nd slide with same graph 9 inches wide and A4 aspect ratio
graph2ppt(file="ggplot2_plot.pptx", width=9, aspectr=sqrt(2), append=TRUE) 
# add 3rd slide with same graph with fixed width & height
graph2ppt(file="ggplot2_plot.pptx", width=6, height=5, append=TRUE) 
# export to Word
graph2doc()
# export to bitmap or vector formats
graph2svg()
graph2png()
graph2tif()
graph2jpg()

## export of aov Anova output
fit=aov(yield ~ block + N * P + K, npk)
x=summary(fit)
# export to Powerpoint
table2ppt(x=x)
table2ppt(x=x,file="table_aov.pptx")
table2ppt(x=x,file="table_aov.pptx",digits=4,append=TRUE)
table2ppt(x=x,file="table_aov.pptx",digits=4,digitspvals=1,font="Times New Roman",pointsize=16,append=TRUE)
# export to Word
table2doc(x=x)
# export to Excel
table2excel(x=x, file = "table_aov.xlsx",digits=4,digitspvals=1,sheetName = "Anova_table", add.rownames = TRUE)
# export to Latex
table2tex(x=x)
# export to HTML
table2html(x=x)

An example Rscript

by liuyujie0136

## Export plots to PPT
# library package "export"
library(export)

# get system time for suitable file name
t=as.character(Sys.time())
t=gsub(" ","-",t)
t=gsub(":","-",t)
fname=paste0("Rplot-",t,".pptx")

# export plots
graph2ppt(file=fname)

对数据框的不同列循环作图

使用aes_string

library(ggplot2)
data <- data.frame(x = c(1, 2, 3),
                   y1 = c(1, 3, 4),
                   y2 = c(2, 5, 7),
                   y3 = c(5, 2, 9))
for (y in c("y1", "y2", "y3")) {
  p <- ggplot(data = data, aes_string(x = "x", y = y)) +
    geom_point()
  print(p)
}

Use coord_cartesian instead of scale_y_continuous

Example:

ggplot(df, aes(x = Group, y = Count)) +
    geom_boxplot(outlier.colour = NA) + 
    coord_cartesian(ylim = c(0, 100))

From the coord_cartesian documentation:

Setting limits on the coordinate system will zoom the plot (like you're looking at it with a magnifying glass), and will not change the underlying data like setting limits on a scale (e.g. scale_y_continuous) will.

You can also use scale_y_continuous alongside coord_cartesian to modify breaks, minor_breaks and expand etc. Just don't supply it with the ylim argument!

在散点图上添加线性拟合方程和R值

借用ggpubr包

library(ggplot2)
library(ggpubr)

set.seed(1234)
df <- data.frame(x = c(1:100))
df$y <- 2 + 3 * df$x + rnorm(100, sd = 40)

p1 <- ggplot(data = df,
             mapping = aes(x = x,
                           y = y)) +
  geom_point() +
  geom_smooth(method = "lm") +
  theme_classic() +
  labs(x = "X",
       y = "Y") +
  theme(axis.title = element_text(size = 10)) +
  stat_cor(label.y = 300,
           aes(label = paste(..rr.label.., ..p.label.., sep = "~`,`~"))) +
  stat_regline_equation(label.x = 5, label.y = 280)

ggsave("p1.pdf",
       annotate_figure(p1, fig.lab = "(a)", fig.lab.size = 20),
       height = 4,
       width = 4)

ggplot2多子图对齐坐标轴

https://zhuanlan.zhihu.com/p/161401082

使用cowplot::plot_grid(align = "vh")，（align = "v"：垂直方向上对齐，align = "h"：水平方向上对齐）

例：plot_grid(p1, p2, p3, p4, ncol = 2, align = "vh")

另，可用于 ggplot2 子图排版的 package 有：

  • gridExtra

  • patchwork

  • cowplot

ggplot2多子图合并图例

https://wilkelab.org/cowplot/articles/shared_legends.html

使用cowplot::get_legend()和cowplot::plot_grid()，示例如下：

library(ggplot2)
library(cowplot)

# plot something first ......

# arrange the three plots in a single row
prow <- plot_grid(
  p1 + theme(legend.position="none"),
  p2 + theme(legend.position="none"),
  p3 + theme(legend.position="none"),
  align = "vh",
  labels = c("A", "B", "C"),
  nrow = 1
)

# extract the legend from one of the plots
legend_a <- get_legend(
  # create some space to the left of the legend
  p1 + theme(legend.box.margin = margin(0, 0, 0, 12))
)

# add the legend to the row we made earlier. Give it one-third of the width of one plot (via rel_widths).
plot_grid(prow,
          legend_a,
          rel_widths = c(3, .4))

# extract a legend that is laid out horizontally
legend_b <- get_legend(
  p1 + 
    guides(color = guide_legend(nrow = 1)) +
    theme(legend.position = "bottom")
)

# add the legend underneath the row we made earlier. Give it 10% of the height of one plot (via rel_heights).
plot_grid(prow,
          legend_b,
          ncol = 1,
          rel_heights = c(1, .1))
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