Hacking Highcharter: observations per group in boxplots

Highcharts has long been a favourite visualisation library of mine, and I’ve written before about Highcharter, my preferred way to use Highcharts in R. Highcharter has a nice simple function, hcboxplot(), to generate boxplots. I recently generated some for a project at work and was asked: can we see how many observations make up the distribution for each category? This is a common issue with boxplots and there are a few solutions such as: overlay the box on a jitter plot to get some idea of the number of points, or try a violin plot, or a so-called bee-swarm plot. In Highcharts, I figured there should be a method to get the number of observations, which could then be displayed in a tool-tip on mouse-over. There wasn’t, so I wrote one like this. First, you’ll need to install highcharter from Github to make it work with the latest dplyr. Next, we generate a reproducible dataset using the wakefield package. For some reason, we want to look at age by gender, but only for redheads: library(dplyr) library(tidyr) library(highcharter) library(wakefield) library(tibble) set.seed(1001) sample_data <- r_data_frame( n = 1000, age(x = 10:90), gender, hair ) %>% filter(hair == "Red") sample_data %>% count(Gender) ## # A tibble: 2 x 2 ## Gender n ## <fctr> <int> ## 1 Male 62 ## 2 Female 48 Giving us 62 male and 48 female redheads. The tibble package is required because later on, our boxplot function ...
Source: What You're Doing Is Rather Desperate - Category: Bioinformatics Authors: Tags: R statistics Source Type: blogs