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
Author:	Catalina Vallejos [ctb], Louis Aslett [ctb], Simon Rogers [ctb], Camila Rangel Smith [cre, ctb], Helen Duncan Little [aut], Jonathan Yong [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

Documentation:

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 Filtering Logging and errors Preprocessing

Downloads:

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

Linking:

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