1 Load packages
library(tidyverse) # data wrangling
library(gridExtra)
library(grid)
library(gt)2 Show case 1: grid.table
d <- head(iris[,1:3])
grid.table(d)
grid.table does the job nicely.
Just plotting give a somewhat too raw object:
plot(tableGrob(d))
3 Show case 2: tableGrob
The following R code is taken from this source:
GGP <- ggplot(dat = iris, aes( x= Sepal.Width, y = Sepal.Length, colour = Species)) + geom_point()
tab <-
iris %>%
group_by(Species) %>%
summarise(n = n(), Mean = mean(Sepal.Width), SD = sd(Sepal.Width))
grid.arrange(GGP,tableGrob(tab))
4 Show case 3: Reduce whitespace
Let’s get rid of white space.
x <- data.frame(a=1, b= 2)
ss <- tableGrob(x)
#Make a scatterplot of your data
k <- ggplot(x,aes(x=x$"Value 1",y=x$"Value 2")) +
geom_point()
#Arrange them as you want with grid.arrange
grid.arrange(ss)
mytheme <- gridExtra::ttheme_default(
core = list(padding=unit(c(1, 1), "mm"))
)
mytable <- tableGrob(mtcars, theme = mytheme)
grid.arrange(mytable)
5 Show case 4: ggpubr
The package ggpubr offers some nice capabilities for plotting tables as ggplot objects:
library(ggpubr)
ggpubr::ggtexttable(head(mtcars), rows = NULL)
6 Reproducibility
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