Questions

Below visualization have been created using mtcars dataset

  1. Draw a pie chart showing the proportion of cars from the mtcars data set that have different carb values.
data("mtcars")
carb_values <- table(mtcars$carb)
carb_values[1]/sum(carb_values)*100
##      1 
## 21.875
carb_percent<-c()
for (i in 1:6) {
  carb_percent[i] <-as.numeric(carb_values[i]/sum(carb_values)*100)
}
names(carb_percent) <- c("1_carb_percent","2_carb_percent", "3_carb_percent", "4_carb_percent", "6_carb_percent", "8_carb_percent")
pie(carb_percent, names(carb_percent))

  1. Draw a bar graph, that shows the number of each gear type in mtcars.
totalGears <- table(mtcars$gear)
barplot(totalGears, main = " Count v/s Gear", xlab = "Gears", ylab = "Count" , col = c("green","yellow", "brown"))

  1. Next show a stacked bar graph of the number of each gear type and how they are further divded out by cyl.
stack <- table(mtcars$cyl, mtcars$gear)
stack
##    
##      3  4  5
##   4  1  8  2
##   6  2  4  1
##   8 12  0  2
barplot(stack, totalGears, xlab = " Gears", ylab= "Count",main = "Stacked barplot of cylinders by gears", col=c("blue","lightgreen","yellow"))

  1. Draw a scatter plot showing the relationship between wt and mpg.
plot(mtcars$wt, mtcars$mpg, main = "mpg v/s wt", ylab = "miles per gallon", xlab = "weight (1000 lbs)")

  1. Design a visualization of your choice using the data.
stack2 <- table(mtcars$am, mtcars$gear)
rownames(stack2) <- c("automatic", "manual")
stack2
##            
##              3  4  5
##   automatic 15  4  0
##   manual     0  8  5
## based on the matrix we can draw a stacked bar plot 
barplot(stack2, totalGears, xlab = " Gears", ylab= "Count",main = "Stacked barplot of transmission by gears", col=c("red","lightgreen"))

We can see infer that, all the cars that are 3 gears are automatic transmission and all the 5 gear cara are manual transmission.