#Part A: Introducing the cars dataset to R
cars=read.table("C:\\Users\\oghen\\Desktop\\cars.txt",header=T,sep = ",")
str(cars)
## 'data.frame': 261 obs. of 8 variables:
## $ mpg : num 14 31.9 17 15 30.5 23 13 14 25.4 37.7 ...
## $ cylinders : int 8 4 8 8 4 8 8 8 5 4 ...
## $ cubicinches: int 350 89 302 400 98 350 351 440 183 89 ...
## $ hp : int 165 71 140 150 63 125 158 215 77 62 ...
## $ weightlbs : int 4209 1925 3449 3761 2051 3900 4363 4312 3530 2050 ...
## $ time.to.60 : int 12 14 11 10 17 17 13 9 20 17 ...
## $ year : int 1972 1980 1971 1971 1978 1980 1974 1971 1980 1982 ...
## $ brand : Factor w/ 3 levels " Europe."," Japan.",..: 3 1 3 3 3 3 3 3 1 2 ...
head(cars)
## mpg cylinders cubicinches hp weightlbs time.to.60 year brand
## 1 14.0 8 350 165 4209 12 1972 US.
## 2 31.9 4 89 71 1925 14 1980 Europe.
## 3 17.0 8 302 140 3449 11 1971 US.
## 4 15.0 8 400 150 3761 10 1971 US.
## 5 30.5 4 98 63 2051 17 1978 US.
## 6 23.0 8 350 125 3900 17 1980 US.
#PART B" :Create a new column converting the ‘time.to.60’ variable from seconds to minutes.
summary(cars$time.to.60)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.00 14.00 16.00 15.55 17.00 25.00
cars$time_minutes <- round(cars$time.to.60/60,1)
#Part c:Remove the columns year, brand, mpg, and hp
cars$year<-NULL
cars$brand<-NULL
cars$mpg<- NULL
cars$hp <- NULL
#Part d: Create a new column performing a min-max transformation on the weightlbs.
cars$weightlb_transformed <- round((cars$weightlbs - min(cars$weightlbs))/(max(cars$weightlbs)-min(cars$weightlbs)),2)
hist(cars$weightlbs)
hist(cars$weightlb_transformed)
#Part e:
print(head(cars,10))
## cylinders cubicinches weightlbs time.to.60 time_minutes
## 1 8 350 4209 12 0.2
## 2 4 89 1925 14 0.2
## 3 8 302 3449 11 0.2
## 4 8 400 3761 10 0.2
## 5 4 98 2051 17 0.3
## 6 8 350 3900 17 0.3
## 7 8 351 4363 13 0.2
## 8 8 440 4312 9 0.2
## 9 5 183 3530 20 0.3
## 10 4 89 2050 17 0.3
## weightlb_transformed
## 1 0.77
## 2 0.09
## 3 0.54
## 4 0.63
## 5 0.13
## 6 0.68
## 7 0.81
## 8 0.80
## 9 0.57
## 10 0.13