mtcars {datasets} | R Documentation

## Motor Trend Car Road Tests

### Description

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

    mtcars

### Format

A data frame with 32 observations on 11 (numeric) variables.

[, 1] | mpg | Miles/(US) gallon
[, 2] | cyl | Number of cylinders
[, 3] | disp | Displacement (cu.in.)
[, 4] | hp | Gross horsepower
[, 5] | drat | Rear axle ratio
[, 6] | wt | Weight (1000 lbs)
[, 7] | qsec | 1/4 mile time
[, 8] | vs | Engine (0 = V-shaped, 1 = straight)
[, 9] | am | Transmission (0 = automatic, 1 = manual)
[,10] | gear | Number of forward gears
[,11] | carb | Number of carburetors

### 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.’

### Source

Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.

### Examples

    require(graphics)
    pairs(mtcars, main = "mtcars data", gap = 1/4)
    coplot(mpg ~ disp | as.factor(cyl), data = mtcars,
           panel = panel.smooth, rows = 1)
    ## possibly more meaningful, e.g., for summary() or bivariate plots:
    mtcars2 <- within(mtcars, {
       vs <- factor(vs, labels = c("V", "S"))
       am <- factor(am, labels = c("automatic", "manual"))
       cyl  <- ordered(cyl)
       gear <- ordered(gear)
       carb <- ordered(carb)
    })
    summary(mtcars2)

[Package datasets version 3.6.1 Index]