The tab function provides a frequency table for a categorical variable. Many options are available.
The cardata data frame contains information on 11,914 vehicles, including make, model, and features and price. First, let’s tabulate the number of automobiles by drive type.
tab(cardata, driven_wheels)
#> level n percent
#> all wheel drive 2353 19.75%
#> four wheel drive 1403 11.78%
#> front wheel drive 4787 40.18%
#> rear wheel drive 3371 28.29%Next, lets add a Total category.
tab(cardata, driven_wheels, total=TRUE)
#> level n percent
#> all wheel drive 2353 19.75%
#> four wheel drive 1403 11.78%
#> front wheel drive 4787 40.18%
#> rear wheel drive 3371 28.29%
#> Total 11914 100%Next, we’ll tabulate the cars by driven_wheels and sort the results in descending order.
tab(cardata, driven_wheels, total=TRUE, sort=TRUE)
#> level n percent
#> front wheel drive 4787 40.18%
#> rear wheel drive 3371 28.29%
#> all wheel drive 2353 19.75%
#> four wheel drive 1403 11.78%
#> Total 11914 100%Next, let’s tabulate the automobiles by make, sorting from largest number to smallest number. We’ll also remove all missing observations from the data set, add a total row, and limit the makes to the 10 most frequent, plus an “Other” category.
tab(cardata, make, sort = TRUE, na.rm = TRUE, total = TRUE, maxcat=10)
#> level n percent
#> Chevrolet 1123 9.43%
#> Ford 881 7.39%
#> Volkswagen 809 6.79%
#> Toyota 746 6.26%
#> Dodge 626 5.25%
#> Nissan 558 4.68%
#> GMC 515 4.32%
#> Honda 449 3.77%
#> Mazda 423 3.55%
#> Cadillac 397 3.33%
#> Other 5387 45.22%
#> Total 11914 100%Finally, let’s list the makes that have at least 5% of the cars, combining the rest into an “Other” category.
tab(cardata, make, minp=0.05)
#> level n percent
#> Chevrolet 1123 9.43%
#> Dodge 626 5.25%
#> Ford 881 7.39%
#> Toyota 746 6.26%
#> Volkswagen 809 6.79%
#> Other 7729 64.87%Frequency tables are usually represented by bar charts. The function can output frequency plots, and cumulative frequency plots.
tab(cardata, vehicle_style, sort=TRUE, plot=TRUE)
tab(cardata, vehicle_style, sort=TRUE, cum=TRUE, plot=TRUE)