Download R Language Charts Data Visualization Assignment Binus University and more Assignments Data Mining in PDF only on Docsity!
NIM: 2602107650
Types of Charts Create your own charts and write the insights! Distribution Script: par ( cex=1. ) hist(mtcars$mpg, col="Red", breaks=9, xlab="MPG", ylab="Frequency", main="Distribution of Cars' MPG" ) Insights: Based on the mtcars dataset, there are many cars that have Miles/(US) Gallon (MPG) in the range of 15 to 21. Script: par ( cex=0. ) boxplot(mpg ~ cyl, data = mtcars, xlab="Number of Cylinders", ylab="MPG", main="Data Distribution Based on The Number of Cylinders and MPG", col="Purple" ) Insights: We can see here on the dataset that the more cylinders a car has, the more likely that car has lower MPG.
NIM: 2602107650
Composition Script: par ( cex=0. 8 ) x1 = sum(mtcars$cyl==4) x2 = sum(mtcars$cyl==6) x3 = sum(mtcars$cyl==8) y1 = (x1/(x1+x2+x3))* y2 = (x2/(x1+x2+x3))* y3 = (x3/(x1+x2+x3))* pie( c(y1, y2, y3), labels=c(paste(y1, "%"), paste(y2, "%"), paste(y 3 , "%")), main="Number of Cylinders Composition", col=rainbow( 3 ) ) legend("topleft", c("4 Cylinders", " Cylinders", "8 Cylinders"), fill=rainbow(3)) Insights: Based on the dataset, almost 50% of the cars have 8 cylinders while the other cars have only 4 or 6 cylinders. Script: par ( cex=0. 8 ) x1 = sum(mtcars$carb==1) x2 = sum(mtcars$carb==2) x3 = sum(mtcars$carb==3) x4 = sum(mtcars$carb==4) x5 = sum(mtcars$carb==6) x6 = sum(mtcars$carb==8) y1 = (x1/(x1+x2+x3+x4+x5+x6))* y2 = (x2/(x1+x2+x3+x4+x5+x6))* y3 = (x3/(x1+x2+x3+x4+x5+x6))* y4 = (x4/(x1+x2+x3+x4+x5+x6))* y5 = (x5/(x1+x2+x3+x4+x5+x6))* y6 = (x6/(x1+x2+x3+x4+x5+x6))* pie( c(y1, y2, y3, y4, y5, y6), labels=c(paste(y1, "%"), paste(y2, "%"), paste(y3, "%"), paste(y4, "%"), paste(y5, "%"), paste(y6, "%")), main="Number of Carburetor Barrels Composition", col=rainbow(6) ) legend("topleft", c("1", "2", "3", "4", "6", "8"), fill=rainbow(6)) Insights: Based on the data visualization above, we can see that cars with 4 carburetor barrels are the majority followed by cars with 2 and 1 carburetor barrels.
NIM: 2602107650
table, col=c("Red", "Blue", "Green"), xlab="Number of Gears", ylab="Frequency", main="Number of Cars Based on The Number of Gears", ) Insights: Based on the dataset, cars with 3 gears are the majority of cars followed by cars that have 4 and then 5 gears. xlab="Year", ylab="Sunspot Number", main="Sunspot Number from 1700 until 1988" ) Insights: We can see here from the dataset that the sunspot number kept changing up and down very often.
