cleanepi: Clean and Standardize Epidemiological Data

Cleaning and standardizing tabular data package, tailored specifically for curating epidemiological data. It streamlines various data cleaning tasks that are typically expected when working with datasets in epidemiology. It returns the processed data in the same format, and generates a comprehensive report detailing the outcomes of each cleaning task.

Package details

AuthorKarim Mané [aut, cre] (<https://orcid.org/0000-0002-9892-2999>), Thibaut Jombart [ctb] (Thibault contributed in development of date_guess().), Abdoelnaser Degoot [aut] (<https://orcid.org/0000-0001-8788-2496>), Bankolé Ahadzie [aut], Nuredin Mohammed [aut], Bubacarr Bah [aut] (<https://orcid.org/0000-0003-3318-6668>), Hugo Gruson [ctb, rev] (<https://orcid.org/0000-0002-4094-1476>), Pratik R. Gupte [rev] (<https://orcid.org/0000-0001-5294-7819>), James M. Azam [rev] (<https://orcid.org/0000-0001-5782-7330>), Joshua W. Lambert [rev] (<https://orcid.org/0000-0001-5218-3046>), Chris Hartgerink [rev] (<https://orcid.org/0000-0003-1050-6809>), Andree Valle-Campos [rev, ctb] (<https://orcid.org/0000-0002-7779-481X>), London School of Hygiene and Tropical Medicine, LSHTM [cph] (00a0jsq62), data.org [fnd]
MaintainerKarim Mané <karim.mane@lshtm.ac.uk>
LicenseMIT + file LICENSE
Version1.1.0
URL https://epiverse-trace.github.io/cleanepi/ https://github.com/epiverse-trace/cleanepi
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("cleanepi")

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cleanepi documentation built on April 4, 2025, 5:12 a.m.