Shell plot

(for visualizing positively skewed longitudinal data)

Static Demo of shell plot

Introduction

This repository introduces a new plot type for positively skewed longitudinal data. It is written for the R statistical language. Contact me on LinkedIn for help or suggestions.

See the tutorial on how to prepare this or similar interactive plot from scratch plus some examples.

Quick start

Clone this repository
Copy the shell subfolder and make it a subfolder of your R project
Start from longitudinal data and make sure individual events have Start and End times (or distances, …) grouped by Subject (one composite annulus in the plot)

library(data.table)
library(magrittr)

waves <- fread("dat/waves.tsv", sep = "\t")

waves[, Start :=  Wave_Distance %>% add(.1) %>% log10]
waves[, End := Start + .1]
waves[, Subject :=  Quake %>% as.character %>% as.factor]

Decide on which variable to use for coloring and create the Group variable accordingly

breaks <- c(-Inf, 1, 2, 5, 10, 25, Inf)
labels <- c("< 1m", "1-2m", "2-5m", "5-10m", "10-25m", "> 25m")

waves[, Group := Wave_Height %>%
    cut(breaks = breaks, labels = labels)]

Provide legend details

layout <- copy(layout_default) # Intrigued about the `copy`? Let me know and I'll explain.

layout$legend <- data.table(
  Id = labels %>% c(NA),
  Label = labels %>% c("(missing)"),
  Color = colorRampPalette(c("steelblue", "orange"))(6) %>%
    c("lightgrey"))
layout$legend_title <- "Wave height"
layout$fx <- -.4
layout$fy <- -.9
layout$s <- .3
layout$unit <- function (x) {
  return(paste0(10 ^ x, "km"))
}

Decide on the hover-over information to show and adjust an infobox template accordingly

<div class="infobox-template" style="display: none;">
  <aside>
    <p class="shell-message">Click episode to copy the data to the clipboard.</p>
    <table class="cycle">
      <caption>Wave {{Wave}}</caption>
      <colgroup>
        <col class="prop-label">
        <col class="prop-value">
      </colgroup>
      <tr>
        <th scope="row">Location</th>
        <td>{{Wave_Province}} ({{Wave_Country}})<br>lat: {{Wave_Latitude}}, lon: {{Wave_Longitude}}</td>
      </tr>
      <tr>
        <th scope="row">Time</th>
        <td>{{Wave_Date}}</td>
      </tr>
      <tr>
        <th scope="row">Height</th>
        <td>{{Wave_Height}} m</td>
...

Knit in Rmarkdown (or write to HTML using %>% write("out/out.html") instead)

waves %>%
  shell_plot (
    width = "500px",
    height = "800px",
    layout = layout,
    infobox_template = "html/waves.html") %>% cat

Often, when we observe natural phenomena, the distribution of the total observation period is long-tailed. This limits the capacity to visualize events that take place during these observations. Several years ago, I realised there is a simple solution for this problem and that is to bend the observation axis into a circle.

Comparison barplot versus shell plot

Now, I revisited this plot and decided to make it using vector-based graphics (SVG) and add some interactivity. I haven't wrapped the code into an R package yet, let me know if you would find it useful.

Cite (thank you)

To site this work:

D'Haese D. (2021) Shellplot for visualizing positively skewed longitudinal data. Accessed on yyy-mm-dd. url: https://github.com/ddhaese/Project_Shell-Plot

Shell plot

Introduction

Quick start

More

Cite (thank you)