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 2022) setting it up as a tibble::tibble() courtesy of (Wickham 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
Wollongong 13.2 17.9 0 NA
WaggaWagga 12.3 22.7 0 4.8
Melbourne 8.2 15.3 0 2.4
MountGinini 16.7 27.3 0 NA
Sydney 13.2 20.9 0 3.4

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://dplyr.tidyverse.org.
Williams, Graham. 2022. Rattle: Graphical User Interface for Data Science in r. https://rattle.togaware.com/.


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