Reading Data

In 2021, a widely shared chart showed U.S. wind and solar capacity "surging past coal." The y-axis started at 50 gigawatts, not zero. Capacity had genuinely grown, but the visual implied a crossover that the underlying numbers did not support. The chart was technically accurate and practically misleading.

Energy policy is argued through charts and statistics. Knowing four common distortions makes it possible to evaluate claims before accepting them.

Truncated y-axes cut the bottom of a chart, magnifying small changes into apparent reversals. Fix: check whether the y-axis starts at zero. Cherry-picked dates select a start or end year that flatters the trend. A renewable cost curve starting in 2010 looks dramatic; starting in 2005 looks less so. Fix: ask what the full historical series shows. Dual y-axes pair two variables on the same chart with independent scales, making any two trends appear to converge or diverge depending on where you set each axis. Fix: request the data in a table or single-axis format. Cumulative vs. annual framing conflates total investment over a decade with this year's investment. Fix: verify whether the number is a stock (cumulative) or a flow (per year).

Worked Example: Reading a solar deployment chart

A chart shows global solar installations tripling from 2015 to 2022. The y-axis begins at 40 GW, and the title says "Solar Surges."

Before accepting the "surge" framing, what should you check first?

Whether the y-axis starts at zero, and whether 40 GW was itself a historically high starting point. If capacity grew from 40 to 120 GW but total global electricity capacity is 8,000 GW, the visual impression outpaces the energy-system reality.

These four questions apply to any chart you encounter in a policy document, a news article, or a think-tank report.

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