Heres the code and output for the set up including library(dplyr) so all the commands would work.
data(mtcars)
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, unionmtcars<- mtcars%>%tibble::rownames_to_column()%>%rename("make_model"=rowname)Now for the output and code for the first question using the commands we learned in class
filter(mtcars, gear=="4") %>% select(make_model,hp,gear) %>% arrange(desc(hp))## make_model hp gear
## 1 Merc 280 123 4
## 2 Merc 280C 123 4
## 3 Mazda RX4 110 4
## 4 Mazda RX4 Wag 110 4
## 5 Volvo 142E 109 4
## 6 Merc 230 95 4
## 7 Datsun 710 93 4
## 8 Fiat 128 66 4
## 9 Fiat X1-9 66 4
## 10 Toyota Corolla 65 4
## 11 Merc 240D 62 4
## 12 Honda Civic 52 4Here’s the select command for the second question.
select(mtcars,make_model,hp)## make_model hp
## 1 Mazda RX4 110
## 2 Mazda RX4 Wag 110
## 3 Datsun 710 93
## 4 Hornet 4 Drive 110
## 5 Hornet Sportabout 175
## 6 Valiant 105
## 7 Duster 360 245
## 8 Merc 240D 62
## 9 Merc 230 95
## 10 Merc 280 123
## 11 Merc 280C 123
## 12 Merc 450SE 180
## 13 Merc 450SL 180
## 14 Merc 450SLC 180
## 15 Cadillac Fleetwood 205
## 16 Lincoln Continental 215
## 17 Chrysler Imperial 230
## 18 Fiat 128 66
## 19 Honda Civic 52
## 20 Toyota Corolla 65
## 21 Toyota Corona 97
## 22 Dodge Challenger 150
## 23 AMC Javelin 150
## 24 Camaro Z28 245
## 25 Pontiac Firebird 175
## 26 Fiat X1-9 66
## 27 Porsche 914-2 91
## 28 Lotus Europa 113
## 29 Ford Pantera L 264
## 30 Ferrari Dino 175
## 31 Maserati Bora 335
## 32 Volvo 142E 109And finally for the average miles per gallon for an automatic car.
filter(mtcars, am=="0") %>% select(am,mpg) %>% summarise(sum(mpg)/19)## sum(mpg)/19
## 1 17.14737And the average mpg for a manual.
filter(mtcars, am=="1") %>% select(am,mpg) %>% summarise(sum(mpg)/13)## sum(mpg)/13
## 1 24.39231