eider
eider: an R package for processing health records declaratively
Science Score: 23.0%
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○CITATION.cff file
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○.zenodo.json file
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2 of 3 committers (66.7%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (20.5%) to scientific vocabulary
Keywords
hut23
hut23-1515
Last synced: 11 months ago
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JSON representation
Repository
eider: an R package for processing health records declaratively
Basic Info
- Host: GitHub
- Owner: alan-turing-institute
- License: other
- Language: R
- Default Branch: main
- Homepage: https://alan-turing-institute.github.io/eider/
- Size: 8.77 MB
Statistics
- Stars: 4
- Watchers: 6
- Forks: 0
- Open Issues: 5
- Releases: 0
Topics
hut23
hut23-1515
Created over 2 years ago
· Last pushed about 2 years ago
Metadata Files
Readme
Changelog
Contributing
License
Code of conduct
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# eider 
**eider** is an R package for extracting machine learning features from tabular data, in particular health records, in a declarative manner.
Features are specified as JSON objects which contain all the necessary information required to perform a given calculation.
For example, the following calculates the number of total rows per patient `id` in the table labelled `ae2` (details on how to specify this table are in the function documentation).
```json
{
"source_table": "ae2",
"transformation_type": "COUNT",
"grouping_column": "id",
"absent_default_value": 0,
"output_feature_name": "total_ae_attendances"
}
```
The output of this is a column named `total_ae_attendances`, containing the number of rows per patient, and with a value of 0 for any patients who do not appear in the `ae2` table.
This declarative approach provides an alternative to traditional, imperative-style, `dplyr` pipelines which can be more difficult to reason about, especially when a series of features is being extracted and merged together.
As features are specified without reference to a specific programming language or paradigm, it also encourages code that is concise, easy to read, and maintainable.
`eider` is a collaboration between The Alan Turing Institute, Public Health Scotland, and the Universities of Edinburgh and Durham.
It grew out of a desire to generalise the feature extraction process for health data, specifically the [SPARRA *(Scottish Patients At Risk of Readmission and Admission)* project](https://www.gov.scot/publications/sparra-made-easy/) ([GitHub repo](https://github.com/jamesliley/SPARRAv4)), and to allow similar analyses to be carried out in different contexts.
## Installation
Install via CRAN:
```r
install.packages("eider")
```
Alternatively, install `eider` from its source code on [GitHub](https://github.com/alan-turing-institute/eider) using:
``` r
install.packages("devtools")
devtools::install_github("alan-turing-institute/eider", build_vignettes = TRUE)
```
## Documentation
The package documentation is available [online](https://alan-turing-institute.github.io/eider/).
In particular, the [package articles](https://alan-turing-institute.github.io/eider/articles/) contain a series of vignettes which provide detailed guidance on the package and its features.
## Development
If you are making changes to the library itself, first clone the repository:
```
git clone git@github.com:alan-turing-institute/eider.git
```
You will need to install the `lintr`, `pkgdown`, `devtools` R packages to build documentation, run tests, and lint.
Then, from the repository root, you can use the following commands:
- `make doc` generates all function documentation, and also generates the `README.md` file from `README.rmd`
- `make lint` lints the project directory
- `make test` runs all tests
You can also use [`pre-commit`](https://pre-commit.com/) to run all of these before committing, to ensure that you do not commit incomplete code.
Firstly, install `pre-commit` according to the instructions on the webpage above.
Then run `pre-commit install`.
*What about vignettes?*
Well, building vignettes is slightly more complicated.
You can perform a one-time build from the R console using `pkgdown::build_site()`, but running this every time you edit a file gets tiring quickly.
To automate this, first install the package with `make install`, and install a working version of Python and also [`entr`](https://github.com/eradman/entr) (the latter is available on Homebrew via `brew install entr`).
Then run `make vig`: this will monitor your vignette RMarkdown files, rebuild the vignettes any time they are changed, and launch a HTTP server on port 8000 to view the files.
If you change any library code you will have to run `make install` again before rerunning `make vig`.
Owner
- Name: The Alan Turing Institute
- Login: alan-turing-institute
- Kind: organization
- Email: info@turing.ac.uk
- Website: https://turing.ac.uk
- Repositories: 477
- Profile: https://github.com/alan-turing-institute
The UK's national institute for data science and artificial intelligence.
GitHub Events
Total
- Watch event: 2
Last Year
- Watch event: 2
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Jonathan Yong | y****e@g****m | 186 |
| Helen Duncan | h****n@t****k | 80 |
| Louis Aslett | l****t@d****k | 5 |
Committer Domains (Top 20 + Academic)
durham.ac.uk: 1
turing.ac.uk: 1
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 66
- Total pull requests: 33
- Average time to close issues: 11 days
- Average time to close pull requests: 3 days
- Total issue authors: 3
- Total pull request authors: 3
- Average comments per issue: 1.05
- Average comments per pull request: 0.79
- Merged pull requests: 32
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- yongrenjie (44)
- helendduncan (12)
- louisaslett (1)
Pull Request Authors
- yongrenjie (15)
- helendduncan (13)
- louisaslett (1)
Top Labels
Issue Labels
enhancement (2)
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 469 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 1
- Total maintainers: 1
cran.r-project.org: eider
Declarative Feature Extraction from Tabular Data Records
- Homepage: https://github.com/alan-turing-institute/eider
- Documentation: http://cran.r-project.org/web/packages/eider/eider.pdf
- License: MIT + file LICENSE
-
Latest release: 1.0.0
published about 2 years ago
Rankings
Dependent packages count: 27.8%
Dependent repos count: 35.7%
Average: 49.5%
Downloads: 85.2%
Maintainers (1)
Last synced:
11 months ago
Dependencies
.github/workflows/ci.yml
actions
- actions/checkout v4 composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/publish.yml
actions
- actions/checkout v4 composite
- peaceiris/actions-gh-pages v3 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION
cran
- dplyr * imports
- fs * imports
- jsonlite * imports
- logger * imports
- lubridate * imports
- magrittr * imports
- purrr * imports
- rlang * imports
- stringr * imports
- tibble * imports
- knitr * suggests
- rmarkdown * suggests
- testthat >= 3.0.0 suggests
- tidyr * suggests