Makeover Monday is a social data project where each week the organisers post a link to a chart and its data, and then people rework the chart. Maybe they re-tell the story more effectively, or find a new story in the data.
For this week’s Makeover Monday, the data set was around global exports of drug and medicines from 2013-2016 which comprised of 3 columns: exporter country, export year, and total exports (USD). A fairly simple data set and rather than embarking on a deep analysis, we decided to have some fun with the visualization this week with a red/white “pill” theme and allow interactivity.
Here is what we did:
Table of Contents
We wanted to have a pill for each year from 2013-2016 and having it show the % exports against the world for a selected country. With that in mind, we grabbed the initial columns and then performed a basic Sub Query to append the “World Export (USD)” data as a column. This is because the initial World Export value was only available as a row within the dataset. The % ratio was then calculated with a simple Calculated Field.
Visualizing the Pill
The pill aesthetic was done via a Thermometer chart.
The configuration and styling options for Meter, Thermometer, and Gauge charts are really flexible, so much so that a Thermometer could be turned into a Bullet Chart as well. To achieve the pill aesthetic for our submission, we styled the Thermometer chart with these configurations:
- Outline, Tick Line, Indicator, and Band Color: #cc0000
- Outline Width: 2 px
- Show Tick Lines: Major
- Major Tick Units: 10
- Major Tick Length: 6 px
- Show Value: Yes
- Manual Target: 100
- Show Bulb: No
- Orientation: Horizontal
- Rounded Corners: 100
One Pill, One Year
To make each pill show a particular year, we used Set Analysis to only grab the % ratio for a specific year.
Dynamic Text in a Widget
With the Exporter Country being available as a filter, readers could select a country and see its export % grow or decline over the years with the “pills” on the canvas. To offer some context around monetary values, we also included a text widget that dynamically updated according to the selected country. To achieve this, we utilized Parameter Replacements within a Text Widget.
Parameter Replacements within a Text Widget allow authors to print out filter or column values directly into a Text Widget. Since we only have a one Exporter Country filter in this instance, we refer to it as [filter:1]:
Upon filtering the published chart, readers will then see a dynamic narrative based on their filter selections:
And that’s it for this week!