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 2023) setting it up as a tibble::tibble() courtesy of (Wickham, François, et al. 2023). 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
Williamtown 11.5 16.8 20.2 0.8
SydneyAirport 13.6 17.9 8.2 2.0
MelbourneAirport 21.0 34.1 0.0 14.2
Canberra 15.9 26.0 6.8 NA
Richmond 1.8 20.0 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. 2023. Dplyr: A Grammar of Data Manipulation. https://CRAN.R-project.org/package=dplyr.
Williams, Graham. 2023. Rattle: Graphical User Interface for Data Science in r. https://rattle.togaware.com/.


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