knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

The goal of rat is to ...

Installation

You can install the released version of rat from CRAN with:

install.packages("rat")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("katiepress/rat")

Example

Binding two factors via fbind():

library(testpackage)
## basic example code
a <- factor(c("character", "hits", "your", "eyeballs"))
b <- factor(c("but", "integer", "where it", "counts"))

Simply catenating two factors leads to a result that most don't expect.

c(a, b)

The fbind() function glues two factors together and returns factor.

fbind(a, b)

Often we want a table of frequencies for the levels of a factor. The base table() function returns an object of class table, which can be inconvenient for downstream work.

set.seed(1234)
x <- factor(sample(letters[1:5], size = 100, replace = TRUE))
table(x)

The fcount() function returns a frequency table as a tibble with a column of factor levels and another of frequencies:

fcount(x)

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)

You'll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this. You could also use GitHub Actions to re-render README.Rmd every time you push. An example workflow can be found here: https://github.com/r-lib/actions/tree/master/examples.

You can also embed plots, for example:

plot(pressure)

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.



katiepress/rat documentation built on Dec. 21, 2021, 5:20 a.m.