recipes: Preprocessing and Feature Engineering Steps for Modeling

A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.

Version: 1.1.0
Depends: dplyr (≥ 1.1.0), R (≥ 3.6)
Imports: cli, clock (≥ 0.6.1), generics (≥ 0.1.2), glue, gower, hardhat (≥ 1.4.0), ipred (≥ 0.9-12), lifecycle (≥ 1.0.3), lubridate (≥ 1.8.0), magrittr, Matrix, purrr (≥ 1.0.0), rlang (≥ 1.1.0), stats, tibble, tidyr (≥ 1.0.0), tidyselect (≥ 1.2.0), timeDate, utils, vctrs (≥ 0.5.0), withr
Suggests: covr, ddalpha, dials (≥ 1.2.0), ggplot2, igraph, kernlab, knitr, modeldata (≥ 0.1.1), parsnip (≥ 1.2.0), RANN, RcppRoll, rmarkdown, rpart, rsample, RSpectra, splines2, testthat (≥ 3.0.0), workflows, xml2
Published: 2024-07-04
DOI: 10.32614/
Author: Max Kuhn [aut, cre], Hadley Wickham [aut], Emil Hvitfeldt [aut], Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: NEWS
CRAN checks: recipes results


Reference manual: recipes.pdf
Vignettes: Handling categorical predictors
Ordering of steps
Roles in recipes
Selecting variables
On skipping steps
Introduction to recipes


Package source: recipes_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): recipes_1.1.0.tgz, r-oldrel (arm64): recipes_1.0.10.tgz, r-release (x86_64): recipes_1.1.0.tgz, r-oldrel (x86_64): recipes_1.0.10.tgz
Old sources: recipes archive

Reverse dependencies:

Reverse depends: embed, scimo, shinyrecipes, textrecipes, themis
Reverse imports: actxps, autostats, bestNormalize, card, caret, correlationfunnel, CSCNet, cvms, D2MCS, easyalluvial, finnts,, healthyR.ts, HTRX, MachineShop, MLDataR, modeltime.ensemble, modeltime.resample, nestedmodels, sparseR, stabiliser, stacks, text, tidymodels, tidysdm, timetk, tune, usemodels, viraldomain, viralmodels, viralx
Reverse suggests: additive, agua, applicable, baguette, bayesian, brulee, bundle, butcher, DALEXtra, dann, finetune, hardhat, modelgrid, modeltime, offsetreg, orbital, palmerpenguins, probably, rsample, rules, SomaDataIO, swag, tabnet, tfhub, tidyAML, tidybins, tidyclust, tidydann, vetiver, waywiser, workflows, workflowsets


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