README.md

In yogevherz/plotme: Complex plots made easier

plotme

The {plotme} package provides a human friendly interface for plots that are otherwise quite hard to create in R. Currently only two functions exist, to create {plotly} sunburst and treemap plots, but (hopefully) more is to come.

Installation

devtools::install_github("yogevherz/plotme")

Usage

library(plotme)
library(dplyr)
library(palmerpenguins)

The count_to_sunburst() and count_to_treemap() functions are built to help you quickly create interactive hierarchical {plotly} plots from categorical data. The This can be very handy when exploring new datasets. The functions expect a summary table created by dplyr::count().

Quickly create a sunburst plot:

penguins %>% 
  count(island, species, sex) %>% 
  count_to_sunburst()

To change the hierarchy, simply change the order within the count() call:

penguins %>% 
  count(species, island, sex) %>% 
  count_to_sunburst()

Color groups by number of observations:

penguins %>% 
  count(species, island, sex) %>% 
  count_to_sunburst(fill_by_n = TRUE)

Make group size proportional to the sum of another variable (in this case, the sum of body mass):

penguins %>% 
  count(species, island, sex, wt = body_mass_g) %>% 
  count_to_sunburst(fill_by_n = TRUE)

Or easily create a treemap plot instead:

penguins %>% 
  count(species, island, sex, wt = body_mass_g) %>% 
  count_to_treemap(fill_by_n = TRUE)

yogevherz/plotme documentation built on Dec. 23, 2021, 8:17 p.m.