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fastDummies: Fast Creation of Dummy (Binary) Columns and Rows from Categorical Variables

Creates dummy columns from columns that have categorical variables (character or factor types). You can also specify which columns to make dummies out of, or which columns to ignore. Also creates dummy rows from character, factor, and Date columns. This package provides a significant speed increase from creating dummy variables through model.matrix().

Version: 1.7.4
Depends: R (≥ 2.10)
Imports: data.table, tibble, stringr
Suggests: testthat (≥ 2.1.0), knitr, rmarkdown, covr, spelling
Published: 2024-08-16
DOI: 10.32614/CRAN.package.fastDummies
Author: Jacob Kaplan ORCID iD [aut, cre], Benjamin Schlegel [ctb]
Maintainer: Jacob Kaplan <jkkaplan6 at gmail.com>
BugReports: https://github.com/jacobkap/fastDummies/issues
License: MIT + file LICENSE
URL: https://github.com/jacobkap/fastDummies, https://jacobkap.github.io/fastDummies/
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: fastDummies results

Documentation:

Reference manual: fastDummies.pdf
Vignettes: Making dummy rows with dummy_rows() (source, R code)
Making dummy variables with dummy_cols() (source, R code)

Downloads:

Package source: fastDummies_1.7.4.tar.gz
Windows binaries: r-devel: fastDummies_1.7.4.zip, r-release: fastDummies_1.7.4.zip, r-oldrel: fastDummies_1.7.4.zip
macOS binaries: r-release (arm64): fastDummies_1.7.4.tgz, r-oldrel (arm64): fastDummies_1.7.4.tgz, r-release (x86_64): fastDummies_1.7.4.tgz, r-oldrel (x86_64): fastDummies_1.7.4.tgz
Old sources: fastDummies archive

Reverse dependencies:

Reverse imports: bigDM, bnpa, causalweight, cbcTools, ClusterVAR, CMMs, codez, conText, countts, deepdive, DMCFB, drf, framecleaner, fusedMGM, GenMarkov, getspanel, gscaLCA, jenga, MplusAutomation, naive, NeuralSens, nlive, psyntur, RCTrep, ResIN, reslr, RobinCar, scpi, segen, Seurat, smdi, spinner, spooky, TangledFeatures, tetragon, tidycomm, tidyvpc, TSCI
Reverse suggests: dagitty, logitr, multifear, Statsomat

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.