RBridge_HW2

R Bridge HW 2

Question 1

carprice <- read.csv("https://raw.githubusercontent.com/johnnyboy1287/Carprice/main/carprice.csv")

summary(carprice)

##        X             Type             Min.Price         Price      
##  Min.   : 6.00   Length:48          Min.   : 6.90   Min.   : 7.40  
##  1st Qu.:17.75   Class :character   1st Qu.:11.40   1st Qu.:13.47  
##  Median :29.50   Mode  :character   Median :14.50   Median :16.30  
##  Mean   :36.54                      Mean   :16.54   Mean   :18.57  
##  3rd Qu.:60.25                      3rd Qu.:19.43   3rd Qu.:20.73  
##  Max.   :79.00                      Max.   :37.50   Max.   :40.10  
##    Max.Price      Range.Price       RoughRange         gpm100     
##  Min.   : 7.90   Min.   : 0.000   Min.   :-0.020   Min.   :2.800  
##  1st Qu.:14.97   1st Qu.: 1.700   1st Qu.: 1.705   1st Qu.:3.800  
##  Median :18.40   Median : 3.300   Median : 3.305   Median :4.200  
##  Mean   :20.63   Mean   : 4.092   Mean   : 4.089   Mean   :4.167  
##  3rd Qu.:24.50   3rd Qu.: 5.850   3rd Qu.: 5.853   3rd Qu.:4.550  
##  Max.   :42.70   Max.   :14.600   Max.   :14.600   Max.   :5.700  
##     MPG.city      MPG.highway   
##  Min.   :15.00   Min.   :20.00  
##  1st Qu.:18.00   1st Qu.:26.00  
##  Median :20.00   Median :28.00  
##  Mean   :20.96   Mean   :28.15  
##  3rd Qu.:23.00   3rd Qu.:30.00  
##  Max.   :31.00   Max.   :41.00

mean(carprice$Min.Price)

## [1] 16.53542

mean(carprice$MPG.city)

## [1] 20.95833

median(carprice$Min.Price)

## [1] 14.5

median(carprice$MPG.city)

## [1] 20

Question 2

carprice_DF <- data.frame(carprice)
Type_MPG <- carprice_DF[1:10,c(2,9,10)]
print(Type_MPG)

##       Type MPG.city MPG.highway
## 1  Midsize       22          31
## 2    Large       19          28
## 3    Large       16          25
## 4  Midsize       19          27
## 5    Large       16          25
## 6  Midsize       16          25
## 7  Compact       25          36
## 8  Compact       25          34
## 9   Sporty       19          28
## 10 Midsize       21          29

Question 3

names(Type_MPG)[1] <- paste("Type of Car")
names(Type_MPG)[2] <- paste("MPG City")
names(Type_MPG)[3] <- paste("MPG Highway")
Type_MPG

##    Type of Car MPG City MPG Highway
## 1      Midsize       22          31
## 2        Large       19          28
## 3        Large       16          25
## 4      Midsize       19          27
## 5        Large       16          25
## 6      Midsize       16          25
## 7      Compact       25          36
## 8      Compact       25          34
## 9       Sporty       19          28
## 10     Midsize       21          29

Question 4

summary(Type_MPG)

##  Type of Car           MPG City      MPG Highway  
##  Length:10          Min.   :16.00   Min.   :25.0  
##  Class :character   1st Qu.:16.75   1st Qu.:25.5  
##  Mode  :character   Median :19.00   Median :28.0  
##                     Mean   :19.80   Mean   :28.8  
##                     3rd Qu.:21.75   3rd Qu.:30.5  
##                     Max.   :25.00   Max.   :36.0

print("Median City MPG")

## [1] "Median City MPG"

median(Type_MPG[,2])

## [1] 19

print("Median Highway MPG")

## [1] "Median Highway MPG"

median(Type_MPG[,3])

## [1] 28

print("Mean City MPG")

## [1] "Mean City MPG"

mean(Type_MPG[,2])

## [1] 19.8

print("Mean Highway MPG")

## [1] "Mean Highway MPG"

mean(Type_MPG[,3])

## [1] 28.8

Question 5

Type_MPG[1][Type_MPG[1] == "Large"] <- "Excellent!"

Question 6

Type_MPG

##    Type of Car MPG City MPG Highway
## 1      Midsize       22          31
## 2   Excellent!       19          28
## 3   Excellent!       16          25
## 4      Midsize       19          27
## 5   Excellent!       16          25
## 6      Midsize       16          25
## 7      Compact       25          36
## 8      Compact       25          34
## 9       Sporty       19          28
## 10     Midsize       21          29