Alluvial plots are similar to sankey diagrams and visualise categorical data over multiple dimensions as flows. (Rosvall M, Bergstrom CT (2010) Mapping Change in Large Networks. PLoS ONE 5(1): e8694. <doi:10.1371/journal.pone.0008694> Their graphical grammar however is a bit more complex then that of a regular x/y plots. The 'ggalluvial' package made a great job of translating that grammar into 'ggplot2' syntax and gives you many options to tweak the appearance of an alluvial plot, however there still remains a multi-layered complexity that makes it difficult to use 'ggalluvial' for explorative data analysis. 'easyalluvial' provides a simple interface to this package that allows you to produce a decent alluvial plot from any dataframe in either long or wide format from a single line of code while also handling continuous data. It is meant to allow a quick visualisation of entire dataframes with a focus on different colouring options that can make alluvial plots a great tool for data exploration.
Version: 0.3.2 Depends: R (≥ 3.5) Imports: purrr , tidyr (≥ 1.0.0) , dplyr , forcats , ggalluvial (≥ 0.9.1) , ggplot2 (≥ 3.2.0) , ggridges , RColorBrewer , recipes (≥ 0.1.5) , rlang , stringr , magrittr , tibble , gridExtra , randomForest , progressr , progress Suggests: testthat, covr, ISLR, nycflights13, vdiffr (≥ 0.3.1), pkgdown, mlbench, earth, workflows, future, furrr, e1071, caret, parsnip, vip, rpart, glmnet, xgboost Published: 2023-12-07 DOI: 10.32614/CRAN.package.easyalluvial Author: Bjoern Koneswarakantha [aut, cre] Maintainer: Bjoern Koneswarakantha <datistics at gmail.com> License: CC0 URL: https://github.com/erblast/easyalluvial/ NeedsCompilation: no Language: en-US Materials: NEWS CRAN checks: easyalluvial results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=easyalluvial to link to this page.
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