Week 3 R assignment
Jian Quan Chen
2023-01-07
Question: Is there a relationship between horsepower and fuel efficiency?
- Data Exploration: This should include summary statistics, means, medians, quartiles, or any other relevant information about the data set. Please include some conclusions in the R Markdown text.
gtcars = read.csv("https://raw.githubusercontent.com/LeJQC/Bridge-Course/main/gtcars.csv")
summary(gtcars)## X mfr model year
## Min. : 1.0 Length:47 Length:47 Min. :2014
## 1st Qu.:12.5 Class :character Class :character 1st Qu.:2016
## Median :24.0 Mode :character Mode :character Median :2016
## Mean :24.0 Mean :2016
## 3rd Qu.:35.5 3rd Qu.:2016
## Max. :47.0 Max. :2017
##
## trim bdy_style hp hp_rpm
## Length:47 Length:47 Min. :259.0 Min. :5000
## Class :character Class :character 1st Qu.:414.5 1st Qu.:5800
## Mode :character Mode :character Median :552.0 Median :6500
## Mean :515.0 Mean :6780
## 3rd Qu.:602.5 3rd Qu.:7750
## Max. :949.0 Max. :9000
##
## trq trq_rpm mpg_c mpg_h
## Min. :243.0 Min. :1400 Min. :11.00 Min. :16.00
## 1st Qu.:376.5 1st Qu.:1712 1st Qu.:13.00 1st Qu.:19.25
## Median :436.0 Median :3550 Median :15.00 Median :22.00
## Mean :441.0 Mean :3651 Mean :15.33 Mean :22.20
## 3rd Qu.:508.0 3rd Qu.:5500 3rd Qu.:16.75 3rd Qu.:24.75
## Max. :664.0 Max. :6750 Max. :28.00 Max. :30.00
## NA's :1 NA's :1 NA's :1
## drivetrain trsmn ctry_origin msrp
## Length:47 Length:47 Length:47 Min. : 53900
## Class :character Class :character Class :character 1st Qu.: 86698
## Mode :character Mode :character Mode :character Median : 129900
## Mean : 193929
## 3rd Qu.: 241325
## Max. :1416362
## mean(gtcars$mpg_h,na.rm = TRUE)## [1] 22.19565mean(gtcars$mpg_c, na.rm = TRUE)## [1] 15.32609median(gtcars$mpg_h, na.rm = TRUE)## [1] 22median(gtcars$mpg_c, na.rm = TRUE)## [1] 15mean(gtcars$hp)## [1] 514.9574There are 47 unique cars from year 2014 to 2017 in this data set . The average miles per gallon on the highway of the cars in this data is 22.20 miles per gallon, with a median of 22 medians per gallon. On the other hand, the average miles per gallon in the city is lower at 15.33 miles per gallon, with a median of 15 miles per gallon.
- Data wrangling: Please perform some basic transformations. They will need to make sense but could include column renaming, creating a subset of the data, replacing values, or creating new columns with derived data (for example – if it makes sense you could sum two columnstogether)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniongtcars <- gtcars %>%
mutate(avg_mpg = (mpg_c + mpg_h) /2,
msrp = round(msrp/1000)) %>%
rename(price_k = msrp)
head(gtcars)## X mfr model year trim bdy_style hp hp_rpm trq
## 1 1 Ford GT 2017 Base Coupe coupe 647 6250 550
## 2 2 Ferrari 458 Speciale 2015 Base Coupe coupe 597 9000 398
## 3 3 Ferrari 458 Spider 2015 Base convertible 562 9000 398
## 4 4 Ferrari 458 Italia 2014 Base Coupe coupe 562 9000 398
## 5 5 Ferrari 488 GTB 2016 Base Coupe coupe 661 8000 561
## 6 6 Ferrari California 2015 Base Convertible convertible 553 7500 557
## trq_rpm mpg_c mpg_h drivetrain trsmn ctry_origin price_k avg_mpg
## 1 5900 11 18 rwd 7a United States 447 14.5
## 2 6000 13 17 rwd 7a Italy 292 15.0
## 3 6000 13 17 rwd 7a Italy 264 15.0
## 4 6000 13 17 rwd 7a Italy 234 15.0
## 5 3000 15 22 rwd 7a Italy 245 18.5
## 6 4750 16 23 rwd 7a Italy 199 19.5- Graphics: Please make sure to display at least one scatter plot, box plot and histogram. Don’t be limited to this. Please explore the many other options in R packages such as ggplot2.
#Scatter plot
library(ggplot2)
gtcars %>%
ggplot(aes(x= hp, y = avg_mpg))+
geom_point(color = "green", na.rm = TRUE, size = 3)+
geom_smooth(method = lm, na.rm = TRUE, se = F)+
labs(title = "Horsepower vs. Miles per Gallon", x = "Horsepower", y = "Average Miles per Gallon" )+
theme_classic()## `geom_smooth()` using formula = 'y ~ x'
#Box plot
gtcars %>%
ggplot(aes(x=avg_mpg, y= ctry_origin))+
geom_boxplot(na.rm = TRUE)+
labs(title = "Fuel Efficiency by Country ", x= "Average Miles per Gallon", y = "Country")+
theme_classic()
#Histogram
gtcars %>%
ggplot(aes(hp))+
geom_histogram(na.rm = TRUE, bins= 10, fill = "red", color = "red", alpha = 0.3 )+
labs(title = "Horsepower by Country", x= "Horsepower", y = "Frequency")+
theme_classic()+
facet_wrap(~ctry_origin)
summary(gtcars)## X mfr model year
## Min. : 1.0 Length:47 Length:47 Min. :2014
## 1st Qu.:12.5 Class :character Class :character 1st Qu.:2016
## Median :24.0 Mode :character Mode :character Median :2016
## Mean :24.0 Mean :2016
## 3rd Qu.:35.5 3rd Qu.:2016
## Max. :47.0 Max. :2017
##
## trim bdy_style hp hp_rpm
## Length:47 Length:47 Min. :259.0 Min. :5000
## Class :character Class :character 1st Qu.:414.5 1st Qu.:5800
## Mode :character Mode :character Median :552.0 Median :6500
## Mean :515.0 Mean :6780
## 3rd Qu.:602.5 3rd Qu.:7750
## Max. :949.0 Max. :9000
##
## trq trq_rpm mpg_c mpg_h
## Min. :243.0 Min. :1400 Min. :11.00 Min. :16.00
## 1st Qu.:376.5 1st Qu.:1712 1st Qu.:13.00 1st Qu.:19.25
## Median :436.0 Median :3550 Median :15.00 Median :22.00
## Mean :441.0 Mean :3651 Mean :15.33 Mean :22.20
## 3rd Qu.:508.0 3rd Qu.:5500 3rd Qu.:16.75 3rd Qu.:24.75
## Max. :664.0 Max. :6750 Max. :28.00 Max. :30.00
## NA's :1 NA's :1 NA's :1
## drivetrain trsmn ctry_origin price_k
## Length:47 Length:47 Length:47 Min. : 54.0
## Class :character Class :character Class :character 1st Qu.: 86.5
## Mode :character Mode :character Mode :character Median : 130.0
## Mean : 193.9
## 3rd Qu.: 241.0
## Max. :1416.0
##
## avg_mpg
## Min. :13.50
## 1st Qu.:15.62
## Median :18.50
## Mean :18.76
## 3rd Qu.:20.38
## Max. :28.50
## NA's :1- Meaningful question for analysis: Please state at the beginning a meaningful question for analysis. Use the first three steps and anything else that would be helpful to answer the question you are posing from the data set you chose. Please write a brief conclusion paragraph in R markdown at the end.
Question: Is there a relationship between horsepower and fuel efficiency?
This data set contains information on 47 deluxe automobiles from 2014 to 2017. To measure fuel efficiency, I took the average of the miles per gallon for both city (mpg_c) and highway (mpg_h) driving. Cars with higher miles per gallon are more fuel efficient than cars with lower miles per gallon. One factor that may affect fuel efficiency is horsepower. By plotting the average miles per gallon of each car against the horsepower of that car, it is clear that there is a relationship between fuel efficiency and horsepower: as horsepower increased, the average miles per gallon decreased.
I also created a box plot to determine which country had more fuel efficient vehicles. Without a doubt, cars from Germany are more fuel efficient than cars produced in the United States, United Kingdom, Japan, and Italy. Based on the histogram, Germany produced more cars with less than the average horsepower (515.0) than the other countries.