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https://github.com/associatedpress/cookiecutter-r-project
Basic cookiecutter template for R projects
https://github.com/associatedpress/cookiecutter-r-project
cookiecutter r
Last synced: 3 months ago
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Basic cookiecutter template for R projects
- Host: GitHub
- URL: https://github.com/associatedpress/cookiecutter-r-project
- Owner: associatedpress
- License: isc
- Created: 2017-01-19T23:27:17.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2024-01-11T22:14:09.000Z (10 months ago)
- Last Synced: 2024-06-04T23:01:54.573Z (5 months ago)
- Topics: cookiecutter, r
- Language: Python
- Size: 29.3 KB
- Stars: 30
- Watchers: 11
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - associatedpress/cookiecutter-r-project - Basic cookiecutter template for R projects (Python)
README
# AP R Cookiecutter
This is a project template powered by [Cookiecutter](https://github.com/cookiecutter/cookiecutter) for use with [datakit-project](https://github.com/associatedpress/datakit-project/).
## Structure
```
.
├── .Rprofile
├── .gitignore
├── README.md
├── analysis
│ └── archive
│ └── markdown
├── data
│ ├── documentation
│ ├── handmade
│ ├── html_reports
│ ├── processed
│ ├── public
│ └── source
├── etl
├── publish
├── scratch
├── viz
└── {{cookiecutter.project_slug}}.Rproj
```
- `.Rprofile`
- Stores environment variables for local R projects.
- `.gitignore`
- Ignores `packrat` and R user profile temporary files.
- `README.md`
- Project-specific readme with boilerplate for data projects.
- Includes sourcing details and places to explain how to replicate/remake the project.
- `analysis`
- R code that involves analysis on already-cleaned data. Code for cleaning data should go in `etl`.
- Multiple analysis files are numbered sequentially.
- If we are sharing the data, last analysis script is called make_dw_files.R to write_csv to public folder.
- `analysis/archive`
- Any analyses for story threads that are no longer being investigated are placed here for reference.
- `analysis/markdown`
- Any R Markdown files go here.
- The AP has an R Markdown template here: https://github.com/associatedpress/apstyle
- `data`
- This is the directory used with our `datakit-data` plugin.
- `data/documentation`
- Documentation on data files should go here - data dictionaries, manuals, interview notes.
- `data/handmade`
- Manually created data sets by reporters go here.
- `data/html_reports`
- Any HTML reports or pages generated by code should go here. These are usually RMarkdown reports for sharing with reporters.
- `data/processed`
- Data that has been processed by scripts in this project and is clean and ready for analysis goes here.
- `data/public`
- Public-facing data files (i.e., final datasets we share with reporters/make accessible) go here - data files which are 'live'.
- `data/source`
- Original data from sources goes here.
- `etl`
- ETL (extract, transform, load) scripts for reading in source data and cleaning and standardizing it to prepare for analysis go here.
- Multiple etl files are numbered.
- Joins are included in etl process.
- Last step of ETL process is to output an RDS file to data/processed.
- naming convention: etl_WHATEVERNAME.rds
- `publish`
- This directory holds all documents in the project that will be public facing (e.g. data.world RMarkdown files).
- `scratch`
- This directory contains scratch materials that will not be used in the project at the end.
- Common cases are filtered tables or quick visualizations for reporters.
- This directory is not tracked in git.
- `viz`
- Graphics and visualization development specific work such as web interactive code should go here.
- `{{cookiecutter.project_slug}}.Rproj`
- This is the .Rproj file that can be used with RStudio to work within the project.
## Usage
You will need to clone this repository to `~/.cookiecutters/` (make the directory if it doesn't exist):
```
cd path/to/.cookiecutters
git clone [email protected]:associatedpress/cookiecutter-r-project
```
Then, use `datakit project`:
```
datakit project create --template cookiecutter-r-project
```
If you'd like to avoid specifying the template each time, you can edit `~/.datakit/plugins/datakit-project/config.json` to use this template by default:
```
{"default_template": "/Users/lfenn/.cookiecutters/cookiecutter-r-project"}
```
## Configuration
You can set the default name, email, etc. for a project in the `cookiecutter.json` file.