Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
Version: 1.1.1 Depends: R (≥ 3.6.0) Imports: data.table, lubridate, stringr, Matrix, progress Suggests: testthat (≥ 2.0.0) Published: 2023-07-04 DOI: 10.32614/CRAN.package.dataPreparation Author: Emmanuel-Lin Toulemonde [aut, cre] Maintainer: Emmanuel-Lin Toulemonde <el.toulemonde at protonmail.com> BugReports: https://github.com/ELToulemonde/dataPreparation/issues License: GPL-3 | file LICENSE NeedsCompilation: no Materials: NEWS CRAN checks: dataPreparation results Documentation: Reference manual: dataPreparation.pdf Downloads: Package source: dataPreparation_1.1.1.tar.gz Windows binaries: r-devel: dataPreparation_1.1.1.zip, r-release: dataPreparation_1.1.1.zip, r-oldrel: dataPreparation_1.1.1.zip macOS binaries: r-release (arm64): dataPreparation_1.1.1.tgz, r-oldrel (arm64): dataPreparation_1.1.1.tgz, r-release (x86_64): dataPreparation_1.1.1.tgz, r-oldrel (x86_64): dataPreparation_1.1.1.tgz Old sources: dataPreparation archive Linking:Please use the canonical form https://CRAN.R-project.org/package=dataPreparation to link to this page.
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