https://github.com/bdcaf/cookiecutter-r-data-analysis

cookie cutter template for my r workflow
https://github.com/bdcaf/cookiecutter-r-data-analysis

cookiecutter makefile r workflow

Last synced: 3 months ago
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cookie cutter template for my r workflow

• Host: GitHub
• URL: https://github.com/bdcaf/cookiecutter-r-data-analysis
• Owner: bdcaf
• License: mit
• Created: 2017-02-27T10:47:40.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2020-02-09T14:44:36.000Z (over 4 years ago)
• Last Synced: 2024-06-17T21:53:23.438Z (5 months ago)
• Topics: cookiecutter, makefile, r, workflow
• Language: TeX
• Size: 71.3 KB
• Stars: 18
• Watchers: 2
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
R data analysis template

========================

Over years I came up with a quite standardized template. Though it usually degraded to copying a number of files from previous projects.  With this template I try to formalize this approach.

[cookiecutter](https://github.com/audreyr/cookiecutter) is a tool to template new project files and folder structures.  It still seems quite active and has templates beyond a single language it seems a promising home for this task.

These templates also contain some sample code for my reference how to achieve typical tasks.  The most code is written in R files and derivatives like `.Rmd` and `.Rnw`.  But I also make use of `make` for building the project, and additionale shell utilities like `latexmk` and `pandoc`.  At some future point I will provide a setup script - at the moment you will need to weed through dependencies manually.

Requirements

------------

Install `cookiecutter` command line: `pip install cookiecutter`

Or with [homebrew](https://brew.sh/) `cookiecutter` command line: `brew install cookiecutter`

Usage

-----

Generate a new Cookiecutter template layout: `cookiecutter gh:bdcaf/cookiecutter-r-data-analysis`.

It creates a minimal project that can be run typing `make`.

Explore the `Readme.md` in the generated directory for more.  

If your `.cookiecutterrc` is configured a quicker start is:

 `cookiecutter gh:bdcaf/cookiecutter-r-data-analysis project_name="This is Magic"`

**Note**

Many functions used require that the project is a valid R package.

The slug must be a valid package name, therefore it must only consist of characters, numbers and `.`, also it must start with a character.

I wrote a simple replacement for spaces to dots, but for the rest you are on your own!

Requirements

------------

Besides `cookiecutter`s dependencies it uses `make`, a `perl` script for dependency discovery. 

Obviously a working `R` installation is also required.

To have the automatic loading of code in `R` the `devtools` package is required. 

For the creation of reports `knitr` is required.

The exemplary work flow has plenty of dependencies. The main ones are:

 - `R` with `knitr`, `pander`, `dplyr`, `ggplot` packages

 - `pandoc` to convert into Word file

 - `latex` for pdf generation

 - `curl` to download the example data

License

-------

This project is licensed under the terms of the [MIT License](/LICENSE)