The usual Premier league table gives a good idea of the ranking, but the gaps between teams aren’t immediately obvious1. I love how this visualisation shows both the rankings and the gaps with one simple line.
Saw this chart – on prices in a car segment in the US – in this article in The Economist. I just couldn’t get over how grossly it misrepresented the data, so here’s the crib.
On a quick look, the chart above seems to indicate that the US government discounts electic car prices by anywhere from 37.5% (BMW i3) to 60% (Tesla Model 3) of the total price – the ratio of light blue bar segment to total.
The reason for this apparent fallacy is the cropped axis on which the values are plotted – instead of starting from zero, it starts from about $22,500 and goes up to $45,000. Adding to the crime of cropping is the location of the axis labels – in the already text heavy section on top.
Result: most viewers would casually interpret that tax credits form a huge rebate on electric cars.
The interpretation changes quickly when the axis is expanded to start from zero.
The tax credit is now clear as just a small share of the real price – a standard $7,500, whatever the car price – rather than a hefty 60% for a Tesla Model 3.
What’s more, it now highlights how competitively priced the Tesla Model 3 and Chevy Bolt are, even if the price subsidy is removed – only BMW 3 series beats them. And that’s before the running & servicing cost savings are accounted for.
Don’t crop the axis!!
Based on my experience of reading, and creating, countless charts – one of my key learnings is simply:
If the axis are cropped, the chart creator is trying to send a false reading – so dig in deeper.
In the case of this chart, the cropping is compounded by hiding the labels in the text heavy section of the graphic.
It’s either a super lazy job by the chart making (and the editor). Or a case of making the chart fit the story / bias.
I use a spreadsheet (Google Sheet) to collect the data, and analyze trends, and catch (to diagnose) outliers. The same spreadsheet also functions as a JSON-providing backend for data being funneled elsewhere (e.g. for user numbers on this page).
While the analysis part, and the JSON-feed worked well, the data collection part was painful. Google doesn’t provide an API to fetch extension data, so I’ve had to fill the data manually into the spreadsheet every day!
For a long time, I used to open my Chrome Web Store (CWS) developer dashboard every morning, and one-by-one fill in the numbers into the spreadsheet cells. While this was relatively easy, if menial, on the desktop, it’s quite painful on the phone – copying numbers between two apps on the small screen.