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Displaying Data in Graphs
Rung 3 of 4 · The traps

Wrong Graph, and the Lying Axis

Two ways a graph goes wrong: you pick a shape that doesn't suit the data, or you chop the axis to blow a tiny difference out of all proportion. Spot both and you'll never be fooled.


Spot itTab 1: read each little dataset and pick the graph that suits it. Tab 2: flip the axis between "start at 0" and "start at 95" and watch the same three bars tell two very different stories.
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A correct graph and a misleading graph can be built from the very same numbers. The difference is choices — which shape, and where the axis starts.

Trap One — the Wrong Shape for the Data

The first big call is what kind of data you've got. Categorical data is labels with no order and nothing in between — favourite sport, eye colour. Numerical data is actual numbers, often flowing along, like a temperature measured each hour. Categorical data wants columns with gaps, because the categories are separate. Numerical-over-time data wants a line, because the line shows the trend between readings. Put a line on favourite sport and you've drawn a slope between "footy" and "netball" — as if there's something halfway between two sports. There isn't. That line is nonsense.

Say it plainly: separate categories → columns with gaps. A number changing over time → a line. Match the picture to the kind of data.

Trap Two — the Axis That Doesn't Start at Zero

This is the classic con, and you'll see it in ads and dodgy headlines forever. In the toy, three brands score 98, 100 and 103 — practically a tie. Start the y-axis at 0 and the bars look almost identical, which is the honest picture. Now slide the axis up so it starts at 95: suddenly Brand C towers over Brand A, even though it's only about 5% higher. Nothing in the data changed — only the bottom of the axis got chopped off, stretching a tiny gap into a cliff.

The trap: a bar graph whose y-axis doesn't start at 0 exaggerates differences. Always check where the axis begins before you believe the gap.

How to Stay Un-fooled

Two quick habits. First, ask "what kind of data is this?" before choosing a graph — that kills trap one. Second, whenever you meet a bar chart, glance at the very bottom of the axis: if it doesn't start at zero, mentally shrink the differences back down. The numbers on the axis are the truth; the heights are just the picture, and a chopped axis paints a lie.

Us, Thinking Out Loud

Give me a dataset that should be a line, and one that should be columns.

Why might a company want its axis to start at 95 instead of 0?