28.11 Formatting Tables Using Kable
REVIEW Including a typeset table based on a
dataset can be accomplished using knitr::kable(). Here we
will use the larger dataset from
rattle (G. Williams 2026) setting it up as a tibble::tibble()
courtesy of (Wickham, François, et al. 2026). We will then choose specific columns and a
random selection of rows to include in the table. The source text we
include in our .Rnw file is listed in the following code
block.
<<example_kable, echo=TRUE, results="asis">>=
set.seed(42)
library(rattle)
nobs <- nrow(weatherAUS)
obs <- sample(nobs, 5)
vars <- 2:6
ds <- weatherAUS[obs, vars]
kable(ds)
@
The result (also showing the R code since we specified
echo=TRUE) is then:
# Set the seed so that results are repeatable.
set.seed(42)
# Load the package from the local library into the R session.
library(rattle)
# Record metadata for a sample of the dataset.
nobs <- nrow(weatherAUS)
obs <- sample(nobs, 5)
vars <- 2:6
ds <- weatherAUS[obs, vars]
# Generate the appropriate LaTeX code to display the data.
kable(ds)| Location | MinTemp | MaxTemp | Rainfall | Evaporation |
|---|---|---|---|---|
| Sydney | 13.2 | 29.5 | 0.0 | 6.4 |
| Richmond | 10.5 | 27.6 | 0.0 | NA |
| MountGinini | -4.1 | -1.0 | 4.6 | NA |
| Williamtown | 7.0 | 18.4 | NA | NA |
| Penrith | 12.1 | 18.2 | 0.0 | NA |
Since we are working with a random sample and we would like the sampling to be repeatable we have used base::set.seed() to initialise the random number generator to a fixed value.
References
Wickham, Hadley, Romain François, Lionel Henry, Kirill Müller, and Davis Vaughan. 2026. Dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org.
Williams, Graham. 2026. Rattle: R Data Science Supporting Rattle. https://togaware.com/projects/rattle/.
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