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: |
0.2.3 |
| Depends: |
R (≥ 2.10) |
| 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 , caret , progress , gridExtra , randomForest , e1071 |
| Suggests: |
testthat, covr, ISLR, nycflights13, vdiffr (≥ 0.3.1), parcats |
| Published: |
2020-05-07 |
| 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: |
README NEWS |
| CRAN checks: |
easyalluvial results |