Load trees data from datasets library
library(datasets)
tr<-trees
head(tr)
Histogram
hist(tr$Volume, col = 'darkred',main="Your title", xlab="Volume")
Barplot
barplot(tr$Height, names.arg=c(1:31), col='darkgreen')
Boxplot
boxplot(tr$Height, col = 'darkblue', xlab='Height',ylab='Height (m)')
boxplot(tr, col='darkorange')
Scatter plot
plot(tr$Height, tr$Volume, col='#FDAE61', pch=19, xlab='Height', ylab=
'Volume', main='Your title')
plot(tr$Volume,tr$Height, col = factor(tr$Girth[1:6]), pch=19,
xlab='Volume', ylab='Height', main='Your title')
# Legend
legend("topleft",
legend = levels(factor(tr$Girth[1:6])),
pch = 19,
col = factor(levels(factor(tr$Girth[1:6]))))
Line graph
plot(tr$Height,type = "o",col = "darkgreen", xlab = "Day", ylab = "Value",
main = "Your title", ylim = c(0, 85), pch=18, lty=6)
lines(tr$Volume, type = "o", col = "darkblue", pch=19, lty=2)
Piechart
piedata <-c(79.814, 0.023, 16.21, 1.636, 2.318)
class <- c("Barren Land", "Water", "Built-up Area", "Tree", "Grass")
pct <- round(piedata/sum(piedata)*100, 2)
class <- paste(class, pct)
class <- paste(class,"%",sep="")
pie(piedata,labels = class, col=rainbow(5), main="LULC Types in 2013")
If you like the content, please SUBSCRIBE to my channel for the future content
To get full video tutorial and certificate, please, enroll in the course through this link:
https://www.udemy.com/course/r-for-research/?referralCode=B6DCFDE343F0592EA61A
Top comments (0)