The {listdown} package provides functions to programmatically create R Markdown files from named lists. It is intended for data analysis pipelines where the presentation of the results is separated from their creation. For this use case, a data processing (or analysis) is performed and the results are provided in a single named list, organized hierarchically. With the list and a {listdown} object a workflowr, pdf, word, or html page. List element names denote sections, subsections, subsubsection, etc. and the list elements contain the data structure to be presented including graphs and tables. The goal of the package is not to provide a finished, readable document. It is to provide a document with all tables and visualization that will appear (computational components). This serves as a starting point from which a user can organize outputs, describe a study, discuss results, and provide conclusions (narrative components).
{listdown} provides a reproducible means for producing a document with specified computational components. It is most compatible with data analysis pipelines where the data format is fixed but the analyses are either being updated, which may affect narrative components including the result discussion and conclusion, or where the experiment is different, which affects all narrative components If the narrative components are not changing with the data being pushed through your analysis pipeline, then you may be better off writing the R Markdown code manually.
You can install the released version of listdown from CRAN with:
install.packages("listdown")
The development version of {listdown} can be installed from GitHub with:
# install.packages("devtools")
devtools::install_github("kaneplusplus/listdown")
As a toy example, suppose we would like to create an html document
plotting Anscombe’s quartet with each plot having it’s own section. To
construct the document, we will need to two objects. The first is a
presentation list, whose names indicate section (or subsection) titles
and whose elements are the objects to present. The second is a
listdown
object, which describes how the object should be rendered in
the document.
library(listdown)
library(ggplot2)
data(anscombe)
# Create the ggplot objects to display.
pres_list <- list(
Linear = ggplot(anscombe, aes(x = x1, y = y1)) + geom_point() + theme_bw(),
`Non Linear` = ggplot(anscombe, aes(x = x2, y = y2)) + geom_point() + theme_bw(),
`Outlier Vertical`= ggplot(anscombe, aes(x = x3, y = y3)) + geom_point() + theme_bw(),
`Outlier Horizontal` = ggplot(anscombe, aes(x = x4, y = y4)) + geom_point() + theme_bw())
# Save the pres_list object so that it can be used in the R Markdown document.
saveRDS(pres_list, "pres-list.rds")
# Create a listdown object.
ld <- listdown(load_cc_expr = readRDS("pres-list.rds"), # The expression to load pres_list.
package = "ggplot2") # The packages needed to render plots.
# Output an html document to a string.
doc <- c(
as.character(
ld_rmarkdown_header("Anscombe's Quartet",
author = "Francis Anscombe",
date = "1973")),
ld_make_chunks(ld))
cat(paste(doc, collapse = "\n"))
#> ---
#> title: Anscombe's Quartet
#> author: Francis Anscombe
#> date: '1973'
#> output: html_document
#> ---
#>
#> ```{r}
#> library(ggplot2)
#>
#> cc_list <- readRDS("pres-list.rds")
#> ```
#>
#> # Linear
#>
#> ```{r}
#> cc_list$Linear
#> ```
#>
#> # Non Linear
#>
#> ```{r}
#> cc_list$`Non Linear`
#> ```
#>
#> # Outlier Vertical
#>
#> ```{r}
#> cc_list$`Outlier Vertical`
#> ```
#>
#> # Outlier Horizontal
#>
#> ```{r}
#> cc_list$`Outlier Horizontal`
#> ```
The document can then be written to a file, rendered, and viewed with the following code.
library(rmarkdown)
writeLines(doc, file("anscombe.Rmd"))
render("anscombe.Rmd")
browseURL("anscombe.html")
Please note that the {listdown} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.