DataProg - Homework1

Loading the dataset ‘mtcars’ into the dataframe ‘automobile’:

automobile <- mtcars

1. Moving rownames to a column ‘cars.name’ and removing rownames:

automobile$cars.name <- rownames(automobile)
rownames(automobile)<- NULL

2. Adding a column named ‘L100km’ whose values are based on the column ‘mpg’ and deleting ‘mpg’:

automobile$L100km <- automobile$mpg
automobile$mpg <- NULL

3. Changing the ‘am’ column to a factor with levels Automatic and Manual:

automobile$am <- factor(automobile$am, levels = c(0,1), labels = c("Automatic","Manual"))

Displaying the dataframe ‘automobile’ as tibble:

library(tibble)
automobileTibble<- as_tibble(automobile)
print(automobileTibble)

# A tibble: 32 × 12
     cyl  disp    hp  drat    wt  qsec    vs am      gear  carb cars.name L100km
   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <fct>  <dbl> <dbl> <chr>      <dbl>
 1     6  160    110  3.9   2.62  16.5     0 Manual     4     4 Mazda RX4   21  
 2     6  160    110  3.9   2.88  17.0     0 Manual     4     4 Mazda RX…   21  
 3     4  108     93  3.85  2.32  18.6     1 Manual     4     1 Datsun 7…   22.8
 4     6  258    110  3.08  3.22  19.4     1 Autom…     3     1 Hornet 4…   21.4
 5     8  360    175  3.15  3.44  17.0     0 Autom…     3     2 Hornet S…   18.7
 6     6  225    105  2.76  3.46  20.2     1 Autom…     3     1 Valiant     18.1
 7     8  360    245  3.21  3.57  15.8     0 Autom…     3     4 Duster 3…   14.3
 8     4  147.    62  3.69  3.19  20       1 Autom…     4     2 Merc 240D   24.4
 9     4  141.    95  3.92  3.15  22.9     1 Autom…     4     2 Merc 230    22.8
10     6  168.   123  3.92  3.44  18.3     1 Autom…     4     4 Merc 280    19.2
# ℹ 22 more rows

4. Average number of gears:

avgGear<-mean(automobile$gear)
print(avgGear)

[1] 3.6875

5. Rows with cars with horsepower between 200 and 400:

selRows <- automobile[automobile$hp >= 200 & automobile$hp <= 400, ]
print(selRows)

   cyl disp  hp drat    wt  qsec vs        am gear carb           cars.name
7    8  360 245 3.21 3.570 15.84  0 Automatic    3    4          Duster 360
15   8  472 205 2.93 5.250 17.98  0 Automatic    3    4  Cadillac Fleetwood
16   8  460 215 3.00 5.424 17.82  0 Automatic    3    4 Lincoln Continental
17   8  440 230 3.23 5.345 17.42  0 Automatic    3    4   Chrysler Imperial
24   8  350 245 3.73 3.840 15.41  0 Automatic    3    4          Camaro Z28
29   8  351 264 4.22 3.170 14.50  0    Manual    5    4      Ford Pantera L
31   8  301 335 3.54 3.570 14.60  0    Manual    5    8       Maserati Bora
   L100km
7    14.3
15   10.4
16   10.4
17   14.7
24   13.3
29   15.8
31   15.0

6. The car that is most fuel-efficient among 6 cylinder cars:

#Subsetting the dataframe to only include 6-cylinder cars
sixCylCars <- automobile[automobile$cyl == 6, ]
#Finding the row with highest fuel-efficiency
fuelEffCar <- sixCylCars[which.max(sixCylCars$L100km),]
print(fuelEffCar)

  cyl disp  hp drat    wt  qsec vs        am gear carb      cars.name L100km
4   6  258 110 3.08 3.215 19.44  1 Automatic    3    1 Hornet 4 Drive   21.4