plot_hist

helper function used by add_marginal_histograms

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.

Bjoern Koneswarakantha

easyalluvial

Generate Alluvial Plots with a Single Line of Code

plot_hist function

<dl><dt>var</dt>
<dd>character vector, variable name</dd>
<dt>p</dt>
<dd>alluvial plot</dd>
<dt>data_input</dt>
<dd>dataframe used to create alluvial plot</dd>
<dt>...</dt>
<dd>additional arguments for specific alluvial plot types: pred_train
can be used to pass training predictions for model response alluvials</dd></dl>

Arguments

plot histogram of alluvial plot variable — plot_hist

<dl>

<dt>var</dt>
<dd>character vector, variable name</dd>


<dt>p</dt>
<dd>alluvial plot</dd>


<dt>data_input</dt>
<dd>dataframe used to create alluvial plot</dd>


<dt>...</dt>
<dd>additional arguments for specific alluvial plot types: pred_train
can be used to pass training predictions for model response alluvials</dd>

</dl>

plot_hist: plot histogram of alluvial plot variable

Description

Usage

Value

Arguments