https://github.com/lwjohnst86/carpenter
Easily make descriptive statistics tables
https://github.com/lwjohnst86/carpenter
characteristic-tables cran descriptive-statistics r rstats science table tables
Last synced: 9 months ago
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Easily make descriptive statistics tables
- Host: GitHub
- URL: https://github.com/lwjohnst86/carpenter
- Owner: lwjohnst86
- License: other
- Created: 2016-05-13T17:42:12.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2022-08-31T08:04:25.000Z (almost 4 years ago)
- Last Synced: 2025-10-22T05:53:08.137Z (9 months ago)
- Topics: characteristic-tables, cran, descriptive-statistics, r, rstats, science, table, tables
- Language: R
- Homepage: http://carpenter.lukewjohnston.com/
- Size: 125 KB
- Stars: 9
- Watchers: 4
- Forks: 3
- Open Issues: 14
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
# carpenter: Making Tables 
[](https://travis-ci.org/lwjohnst86/carpenter)
[](https://cran.r-project.org/package=carpenter)
[](https://codecov.io/github/lwjohnst86/carpenter?branch=master)
[](https://ci.appveyor.com/project/lwjohnst86/carpenter)
[](https://www.tidyverse.org/lifecycle/#maturing)
[](https://www.r-pkg.org/pkg/carpenter)
The main goal of carpenter to simplify making those pesky descriptive/basic
characteristic tables often used in biomedical journal articles. It was designed
to work well within the tidyverse ecosystem, e.g. relying on using pipes to chain
functions together or having multiple, dedicated functions to use (rather than a
monolithic one with lots of arguments).
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# Installation
This package is on CRAN, so install using:
```{r, eval=FALSE}
install.packages('carpenter')
```
For the developmental version, install from GitHub:
```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github('lwjohnst86/carpenter')
```
# Example usage
Here is an example workflow for making tables:
```{r example}
library(carpenter)
outline_table(iris, 'Species') %>%
add_rows('Sepal.Length', stat_meanSD) %>%
add_rows('Petal.Length', stat_meanSD) %>%
add_rows('Sepal.Width', stat_medianIQR) %>%
build_table()
```
For a more detailed view of how to use carpenter, see `?carpenter` or
`vignette('carpenter')`. Or view the vignette directly [here](https://htmlpreview.github.io/?https://github.com/lwjohnst86/carpenter/blob/master/vignettes/carpenter.html)
# Resources
There are several packages out there that help with making tables. Most of them
work to output and customize the tables into a given format, for instance
markdown or html, but assume the data is in the form you already want to present
it in. So they don't help with getting the data into the form of a table (in
the context of descriptive/basic characteristic tables often seen in biomedical
research). Even still, they are very useful to look over and learn about!
- [`pander`](http://rapporter.github.io/pander/)
- [`pixiedust`](https://cran.r-project.org/package=pixiedust)
- [`stargazer`](https://cran.r-project.org/package=stargazer)
- [`htmlTable`](https://cran.r-project.org/package=htmlTable)
- [`tableone`](https://cran.r-project.org/package=tableone)