CODEWITHSUNDEEP
rggplot2plot
sametsokel
sametsokel

Reputation: 384

Adding individual titles from a vector to each R plots

For a function, I need to keep variable names in a vector and I use a function to plot density graphs of my variables.

My problem is as follows in summary ;

var_names <- c("mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb")

plotter <- function(x){
  
  plot(density(x),
       main = "",
       xlab = "",
       ylab = "")
  title(var_names)
  
  
}

par(mfrow=c(4,3),mar=c(1,1,1,1))

apply(mtcars,2,plotter)

enter image description here

Couldn't imagine how I can match them.

Upvotes: 1

Views: 260

Answers (2)

Bernhard
Bernhard

Reputation: 4427

var_names <- c("mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb")

plotter <- function(x, var){
  
  plot(density(x[[var]]),
       main = var,
       xlab = "",
       ylab = "")
}

par(mfrow=c(4,3),mar=c(2.1,2.1,2.1,1))

for(vn in var_names) plotter(mtcars, vn)

will yield enter image description here

for loops are discouraged as they are slow. However in conjunction with plotting, which is slow in its own way or if the loop is only run for 11 times as in this example, for loops are perfectly fine and beginner friendly.

If you really need an apply-family function of plotters to have only one argument, the following will do:

var_names <- c("mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb")

plotter <- function(x){
  plot(density(x[[1]]),
     main = names(x),
     xlab = "",
     ylab = "")
}

par(mfrow=c(4,3),mar=c(2.1,2.1,2.1,1))

sapply(1:11,function(n) plotter(mtcars[n]))

Upvotes: 2

Duck
Duck

Reputation: 39613

I would suggest a tidyverse approach with ggplot2 and the vector of names you have. You can format your data to longer and then filter the desired variables. Using facets and geom_density() you can avoid issues with titles. Here the code:

library(tidyverse)
#Vector
var_names <- c("mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb")
#Data
mtcars %>% pivot_longer(cols = everything()) %>%
  filter(name %in% var_names) %>%
  ggplot(aes(x=value))+
  geom_density()+
  facet_wrap(.~name,scales = 'free')+
  theme_bw()

Output:

enter image description here

Upvotes: 2

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