Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

CLICK HERE TO VISIT THE UPDATED SURVIVAL GUIDE

Formatting Tables Using Kable

Raw Including a typeset table based on a dataset can be accomplished using knitr::kable(). Here we will use the larger weatherAUS dataset from rattle setting it up as a dplyr::tibble() courtesy of dplyr. 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
Tuggeranong	10.0	25.1	0.2	NA
Wollongong	20.8	30.7	1.0	NA
Dartmoor	5.7	14.9	1.6	2.6
Sale	16.8	28.8	0.0	6.0
WaggaWagga	7.7	31.3	0.0	4.0

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.