Assignment 3

R Markdown

Question 1: Keep only cars with more than 6 cylinders and mpg greater than 15

high_powered_cars<- mtcars %>% # then
  filter(cyl > 6 &  mpg > 15) 

head(high_powered_cars , 3)

##                    mpg cyl  disp  hp drat   wt  qsec vs am gear carb
## Hornet Sportabout 18.7   8 360.0 175 3.15 3.44 17.02  0  0    3    2
## Merc 450SE        16.4   8 275.8 180 3.07 4.07 17.40  0  0    3    3
## Merc 450SL        17.3   8 275.8 180 3.07 3.73 17.60  0  0    3    3

Question 2: Select mpg, hp, wt

efficiency_something <- mtcars %>%
    select(mpg , hp , wt)

head(efficiency_something , 3)

##                mpg  hp    wt
## Mazda RX4     21.0 110 2.620
## Mazda RX4 Wag 21.0 110 2.875
## Datsun 710    22.8  93 2.320

Question 3: rename mpg and hp

renamed_vars <- mtcars %>%
  rename(miles_per_gallon = mpg , horsepower = hp)

head(renamed_vars , 2)

##               miles_per_gallon cyl disp horsepower drat    wt  qsec vs am gear
## Mazda RX4                   21   6  160        110  3.9 2.620 16.46  0  1    4
## Mazda RX4 Wag               21   6  160        110  3.9 2.875 17.02  0  1    4
##               carb
## Mazda RX4        4
## Mazda RX4 Wag    4

Question 4: mutate power to wt ratio

power_wt_ratio <-mtcars %>%
  mutate(power_ratio = hp/wt)

head(power_wt_ratio , 8)

##                    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
## Duster 360        14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
## Merc 240D         24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
##                   power_ratio
## Mazda RX4            41.98473
## Mazda RX4 Wag        38.26087
## Datsun 710           40.08621
## Hornet 4 Drive       34.21462
## Hornet Sportabout    50.87209
## Valiant              30.34682
## Duster 360           68.62745
## Merc 240D            19.43574

Question 5: arrange mpg and transmission: all automatic, then all manual, each sorted by mpg

descending

sorted_data <- mtcars %>%
  arrange(am , desc(mpg) )

head(sorted_data , 3)

##                mpg cyl  disp hp drat    wt  qsec vs am gear carb
## Merc 240D     24.4   4 146.7 62 3.69 3.190 20.00  1  0    4    2
## Merc 230      22.8   4 140.8 95 3.92 3.150 22.90  1  0    4    2
## Toyota Corona 21.5   4 120.1 97 3.70 2.465 20.01  1  0    3    1

Question 6: Combining verbs/functions

combo <- mtcars %>% # then
  filter(cyl > 6 &  mpg > 15) %>%
  select(mpg , hp, wt , am) %>%
  rename(miles_per_gallon = mpg , horsepower = hp) %>%
  mutate(power_ratio = horsepower/wt) %>%
  arrange(am , desc(miles_per_gallon) ) %>%
  select(-am)

head(combo , 8)

##                   miles_per_gallon horsepower    wt power_ratio
## Pontiac Firebird              19.2        175 3.845    45.51365
## Hornet Sportabout             18.7        175 3.440    50.87209
## Merc 450SL                    17.3        180 3.730    48.25737
## Merc 450SE                    16.4        180 4.070    44.22604
## Dodge Challenger              15.5        150 3.520    42.61364
## Merc 450SLC                   15.2        180 3.780    47.61905
## AMC Javelin                   15.2        150 3.435    43.66812
## Ford Pantera L                15.8        264 3.170    83.28076