datatxt provides utilities for working with the data.txt
specification. Currently, it provides a function, narrate(), that
enables automatic generation of data documentation. See
https://datatxtdoc.netlify.com/ for an example.
You can install the development version of datatxt with
# install.packages("remotes")
remotes::install_github("datatxtorg/datatxt")We can generate data documentation by passing the URL of the data.txt
to narrate():
library(datatxt)
temp_dir <- tempdir()
narrate("https://datatxt.org/data.txt", output_dir = temp_dir)
list.files(temp_dir)
#> [1] "iris.md" "mtcars.md"We can then inspect the contents of one of these files:
cat(readLines(file.path(temp_dir, "iris.md")), sep = "\n")
#> ---
#> title: iris
#> ---
#>
#> ## Description
#>
#> This famous (Fisher's or Anderson's) iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.
#>
#> ## Summary
#>
#> Skim summary statistics
#> n obs: 150
#> n variables: 5
#>
#> Variable type: factor
#>
#> variable missing complete n n_unique top_counts ordered
#> ---------- --------- ---------- ----- ---------- ---------------------------------- ---------
#> Species 0 150 150 3 set: 50, ver: 50, vir: 50, NA: 0 FALSE
#>
#> Variable type: numeric
#>
#> variable missing complete n mean sd p0 p25 p50 p75 p100 hist
#> -------------- --------- ---------- ----- ------ ------ ----- ----- ------ ----- ------ ----------
#> Petal.Length 0 150 150 3.76 1.77 1 1.6 4.35 5.1 6.9 ▇▁▁▂▅▅▃▁
#> Petal.Width 0 150 150 1.2 0.76 0.1 0.3 1.3 1.8 2.5 ▇▁▁▅▃▃▂▂
#> Sepal.Length 0 150 150 5.84 0.83 4.3 5.1 5.8 6.4 7.9 ▂▇▅▇▆▅▂▂
#> Sepal.Width 0 150 150 3.06 0.44 2 2.8 3 3.3 4.4 ▁▂▅▇▃▂▁▁