var_cars {ale} | R Documentation |
Multi-variable transformation of the mtcars dataset.
Description
This is a transformation of the mtcars
dataset from R to produce a small
dataset with each of the fundamental datatypes: logical, factor, ordered,
integer, and double. Most of the transformations are obvious, but two are
noteworthy:
For the unordered factor, the country of the car manufacturer is obtained based on the row names of
mtcars
. Thisvar_cars
version does not have row names.For the ordered factor, gears 3, 4, and 5 are encoded as 'three', 'four', and 'five', respectively. The text labels make it explicit that the variable is ordinal, yet the number names make the order crystal clear.
Here is the original description of the mtcars
dataset:
The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models).
Usage
var_cars
Format
A tibble with 32 observations on 12 variables.
- mpg
double
: Miles/(US) gallon- cyl
integer
: Number of cylinders- disp
double
: Displacement (cu.in.)- hp
double
: Gross horsepower- drat
double
: Rear axle ratio- wt
double
: Weight (1000 lbs)- qsec
double
: 1/4 mile time- vs
logical
: Engine (0 = V-shaped, 1 = straight)- am
logical
: Transmission (0 = automatic, 1 = manual)- gear
ordered
: Number of forward gears- carb
integer
: Number of carburetors- country
factor
: Country of car manufacturer
Note
Henderson and Velleman (1981) comment in a footnote to Table 1: 'Hocking (original transcriber)'s noncrucial coding of the Mazda's rotary engine as a straight six-cylinder engine and the Porsche's flat engine as a V engine, as well as the inclusion of the diesel Mercedes 240D, have been retained to enable direct comparisons to be made with previous analyses.'
References
Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.