Package: tidymodlr
Title: An R6 Class to Perform Analysis on Long Tidy Data
Version: 1.0.0
Authors@R: person("David", "Hammond", email = "anotherdavidhammond@gmail.com", role = c("aut", "cre"))
Author: David Hammond [aut, cre]
URL: https://github.com/david-hammond/tidymodlr
BugReports: https://github.com/david-hammond/tidymodlr/issues
Maintainer: David Hammond <anotherdavidhammond@gmail.com>
Description: Transforms long data into a matrix form to allow for ease
        of input into modelling packages for regression, principal
        components, imputation or machine learning. It does this by
        pivoting on user defined columns, generating a key-value table
        for variable names to ensure one-to-one mappings are preserved.
        It is particularly useful when the indicator names in the
        columns are long descriptive strings, for example "Energy
        imports, net (% of energy use)". High level analysis wrapper
        functions for correlation and principal components analysis are
        provided.
License: MIT + file LICENSE
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports: R6, dplyr, tidyr, tm, corrr, FactoMineR
Depends: R (>= 4.1.0)
LazyData: true
Config/pak/sysreqs: cmake libfreetype6-dev make libicu-dev libpng-dev
        libuv1-dev libxml2-dev zlib1g-dev
Repository: https://david-hammond.r-universe.dev
Date/Publication: 2024-08-20 07:06:32 UTC
RemoteUrl: https://github.com/david-hammond/tidymodlr
RemoteRef: HEAD
RemoteSha: d2b8f3835be4a3533ba587af10fa5467e1c38dc4
NeedsCompilation: no
Packaged: 2026-10-05 10:06:05 UTC; root