eider: Declarative Feature Extraction from Tabular Data Records

Extract features from tabular data in a declarative fashion, with a focus on processing medical records. Features are specified as JSON and are independently processed before being joined. Input data can be provided as CSV files or as data frames. This setup ensures that data is transformed in a modular and reproducible manner, and allows the same pipeline to be easily applied to new data.

Version: 1.0.0
Imports: dplyr, lubridate, stringr, magrittr, jsonlite, logger, purrr, fs, tibble, rlang
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), tidyr
Published: 2024-05-13
DOI: 10.32614/CRAN.package.eider
Author: Catalina Vallejos ORCID iD [ctb], Louis Aslett ORCID iD [ctb], Simon Rogers ORCID iD [ctb], Camila Rangel Smith ORCID iD [cre, ctb], Helen Duncan Little ORCID iD [aut], Jonathan Yong ORCID iD [aut], The Alan Turing Institute [cph, fnd]
Maintainer: Camila Rangel Smith <crangelsmith at turing.ac.uk>
BugReports: https://github.com/alan-turing-institute/eider/issues
License: MIT + file LICENSE
URL: https://github.com/alan-turing-institute/eider
NeedsCompilation: no
Materials: README NEWS
CRAN checks: eider results


Reference manual: eider.pdf
Vignettes: Combination features
Introduction to eider
Examples: A&E data
Examples: LTC data
Examples: PIS data
Examples: SMR04 data
An overview of features
Logging and errors


Package source: eider_1.0.0.tar.gz
Windows binaries: r-devel: eider_1.0.0.zip, r-release: eider_1.0.0.zip, r-oldrel: eider_1.0.0.zip
macOS binaries: r-release (arm64): eider_1.0.0.tgz, r-oldrel (arm64): eider_1.0.0.tgz, r-release (x86_64): eider_1.0.0.tgz, r-oldrel (x86_64): eider_1.0.0.tgz


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