The field guide
40 ways a chart can mislead
The techniques that do most of the misleading, grouped by type. Each page explains how the technique works, how to spot it in the wild, and what an honest version of the chart looks like.
Axis crimes
Where most chart lies begin: the humble axis, bent until the data confesses.
The truncated axis
A 3% difference, presented as a landslide.
Bar charts encode value as length, so the baseline has to be zero — chop the bottom off the axis and a bar twice as tall no longer means twice as much. Start the axis at 94 and a one-point gap reads as total domination.
6 exhibits in the gallery
Dual y-axes
Two axes, one narrative, infinite flexibility.
Put one series on the left axis and another on the right, and you get two free knobs to turn until the lines cross exactly where the story needs them to. The correlation you “see” is a design decision, not a finding.
3 exhibits in the gallery
The inverted axis
Up is down. Less is more.
Flip the y-axis so larger values plot lower, and every trend reads backwards. Famously used to make a rise in gun deaths look like a decline — at a glance the chart says the exact opposite of its own numbers.
3 exhibits in the gallery
Uneven intervals
1990, 1995, 2000, 2004, 2006, 2007 — evenly spaced.
Plot irregular time steps at regular spacing and you silently stretch some periods and compress others. Slopes become fiction: a decade and a single year occupy the same width, so the “acceleration” is typography.
5 exhibits in the gallery
The log scale
Every gridline is another ×10, and the eye reads them as equal steps.
A log axis spaces equal ratios equally: 1 to 10 occupies the same width as 1,000 to 10,000. For data that genuinely spans orders of magnitude that is the right tool — but the eye still reads distance as amount, so a thousandfold gap arrives on the page looking like a modest lead. Put bars on one and it gets worse: a bar encodes its value as length from zero, and a log axis has no zero, so every bar’s length is set by wherever the axis was started.
1 exhibit in the gallery
The broken axis
The zero is still there. The middle is missing.
A truncated axis chops the bottom off the scale and announces itself by starting at 94.6. A break does something quieter: it keeps the zero, keeps the top, and takes a slice out of the middle, marking the theft with a small zigzag most readers have been trained to read as a tidying-up. What it removes is not empty space — it is the part of the scale where the difference between the bars actually lives, so lengths on either side of it stop meaning the same thing and the ratio between any two bars becomes whatever the designer’s choice of gap made it. Worse, the two halves are almost never drawn at the same rate: the compressed top buys room for the giant, and every unit up there is worth a fraction of a unit down below.
1 exhibit in the gallery
The clipped axis
Everything taller than the frame is drawn exactly as tall as the frame.
A truncated axis takes the bottom of the scale and a broken axis takes a slice out of the middle. This one takes the top, and it is the quietest of the three, because nothing about the axis looks wrong: the zero survives, the ticks are round, the gridlines are evenly spaced, and there is no zigzag to mark the theft. What has gone is the range above the last tick. The maximum was fixed — a dashboard setting, a target line, a template, a limit typed once and never revisited — and the data was never asked whether it fitted. Every value that runs past the top is drawn at the top, so above the ceiling the mark stops being a measurement and becomes a threshold test: all quantities up there are the same quantity. How it fails depends on the mark — bars, columns, gauges and clamped colour scales arrive flat against the frame, while a line simply leaves it and comes back, which is louder but just as unmeasurable. And unlike the other two, it leaves the reader nothing to work with, because what it removed is not on the chart to be noticed — a truncated axis at least prints the number it starts at, while a ceiling’s whole effect lives in values the picture never mentions.
1 exhibit in the gallery
The aspect ratio
Same numbers, same axis, same range — and the slope is whatever shape the box is.
Every angle on a chart is two exchange rates divided by one another: how many pixels the vertical axis gives a unit of data, over how many the horizontal axis gives a step of time. The labels declare the two ranges and never the shape of the box those ranges are drawn in, so one series, on one scale, over one span, can be squeezed into a tall panel and read as a collapse or stretched into a wide one and read as a drift, with no number moved and no baseline chopped. It is the axis crime that survives a zero baseline, because it is not about where the axis starts but about how far apart the two axes have been pulled — and it is almost never a decision. A dashboard tile, a column width, a slide template, a figure resized to fill the space left over: the container picks the drama, and the caption never mentions that it did.
1 exhibit in the gallery
The rebased index
Every line passes through 100 on a date somebody chose.
Indexing divides every series by its own value in one chosen period and multiplies by 100, which is why it is the standard cure for dual axes: two quantities of different size, in different units, end up on one honest ruler. The cure has a knob. Each series is divided by a different number, so moving the base multiplies each line by a constant of its own — one slides up, the other down — and the gap the reader carries away is a fact about the date in the divisor as much as about the data. The base is also the single point where the chart declares the series equal, so the crossing everybody reads off is a cell in a spreadsheet. And the reading inverts either side of it: to the right of the base the higher line has grown more since the base, while to the left the higher line is the one that grew less on the way to it.
1 exhibit in the gallery
Size & scale
When 2× somehow looks like 8×. Your eye reads ink, not numbers.
The area illusion
Twice the value, four times the ink.
Scale an icon’s or circle’s height by the data and its area grows by the square. A value that doubled looks quadrupled — and in 3D, octupled. Your eye judges the ink, not the radius.
6 exhibits in the gallery
Gratuitous 3D
The slice in front always wins.
Tilt a pie chart into 3D and perspective inflates whatever sits closest to the viewer, with a thick rim thrown in as bonus ink. 3D bars pull the same trick with parallax — nobody can tell where the tops actually are.
3 exhibits in the gallery
The impossible pie
70% + 63% + 60% = one pie chart.
A pie chart promises that its slices sum to a whole. Feed it multi-select survey data — where respondents could pick several answers — and you get confident-looking slices adding up to 193%.
2 exhibits in the gallery
The radar chart
A spoke twice as long paints four times the ink.
A radar chart asks you to judge a row of numbers by the area of the shape they enclose, and area grows as the square of every spoke — so a modest lead in the scores arrives on the page as a commanding blot. Two more knobs hide in the same picture: the radial axis is rarely zero-based, which stretches the spokes before the squaring even starts, and the enclosed area depends on which categories happen to sit opposite each other, so reordering the labels changes the shape without changing a number.
1 exhibit in the gallery
The false common scale
Same word on the axis. Not the same thing being counted.
A bar chart makes exactly one promise: that its lengths are commensurable, because every one of them is so many of the same thing. Put rows on it whose unit quietly changes — counts of objects that do different jobs, figures collected under different rules, quantities that happen to share a word — and the promise is void while the picture looks unchanged. Nothing is exaggerated and no axis is bent; the ranking is simply about a quantity that does not exist.
1 exhibit in the gallery
The stack with one baseline
One band starts at zero. The rest float on whatever is underneath them.
Stacking pours the series into one silhouette, and only the one at the bottom keeps a baseline. Every band above it is the gap between two moving edges, so reading one means subtracting two positions the chart never prints — and where the stack climbs steeply the eye measures the shortest way across the band rather than the vertical way, which shaves it thinner still. Then there is the variant that runs the axis to 100%, and it is the one that does real damage: the total is divided out, so nothing on the page is an amount any more. A series that tripled can only be drawn as a narrowing band if the series beneath it grew faster, and narrowing is what the reader remembers.
1 exhibit in the gallery
The word cloud
The biggest word is usually just the longest one.
A word cloud asks the eye to rank quantities by how big the words look, and a word’s size on the page is set by two things, only one of which is the data. The font size carries the frequency; the letter count carries nothing at all. A word’s footprint is its em square repeated once per letter, so what the reader actually measures is frequency times length — and an eleven-letter word at half the count reliably outdraws a three-letter one. Even the charitable sizing rule, font size set to the square root of the count, which is trying to make area track frequency, only ever governs one of the two dimensions. Around that sit the knobs nobody declares: a stop-word list that decides which words exist at all, a layout seed that rearranges the picture on every run, rotation that shrinks whatever it turns, and colour that usually means nothing while the eye goes on looking for its meaning.
1 exhibit in the gallery
The map projection
Greenland is not bigger than Africa. The map is.
A globe cannot be flattened without something being stretched, and every projection chooses what it will sacrifice. Web Mercator — the one under nearly every map on the internet — keeps angles and local shape, and pays for it in area: it stretches both directions by the secant of the latitude, so it stretches area by the square of that. Every square kilometre is quietly multiplied before you see it, by 1 at the equator, 2 at 45°, 4 at 60° and 33 at 80°, and the eye reads the ink rather than the coordinates. The same arithmetic escapes the picture and turns up as a figure with units on it, because a GIS asked for an area in the coordinate system it happens to be drawing in will answer in square metres of the projection plane and never mention that the plane is not the ground.
1 exhibit in the gallery
The treemap
Thirteen rectangles, no axis, and one area judgement per comparison.
A treemap gives every value a rectangle whose area is exactly proportional to it, and then packs the rectangles together. The arithmetic is impeccable and the job it hands the reader is the hardest one on any chart: area is the product of two dimensions, so nothing you can measure on the page is the value. A tile can be the widest on the chart and the fifth largest, because width is only half of it. There is also nothing to measure against — no axis, no baseline, no gridlines, only neighbours — and the shapes are not even fixed by the data: feed the same numbers to the same layout in a different order and every rectangle changes proportions while its area stays put.
1 exhibit in the gallery
The free-scale small multiple
Six panels in one grid, six different rulers.
A small multiple works by holding everything constant except the data: same chart, same size, same years, same scale, repeated down the page, so that any difference the eye finds is a difference in the numbers. Fit each panel’s axis to its own series and the last of those constants quietly goes, while the picture looks exactly as it did. Every panel is now drawn to its own ruler, so a bar that reaches the top of one frame and a bar that reaches the top of the next are the same height and not the same quantity, and the comparison between panels — the only reason to put the panels in one frame — is invented by the layout. The panels are not individually wrong, which is what makes it hard to see: each is a correct chart of its own series, and the ratios inside a panel survive. It is the ratios across panels, the ones the grid is silently offering, that are a fact about the autoscaler.
1 exhibit in the gallery
The rainbow colour map
One degree buys seventeen units of colour here and half a unit over there.
A colour ramp is an axis: it converts a quantity into an appearance, and the reader converts it back. Lightness is the one channel with an order everybody already agrees on — hue has none until a convention supplies one — and a rainbow ramp does not spend its lightness in order. Jet climbs from dark blue through cyan to a peak in the yellow, then falls away into dark red, so the brightest thing on the chart is a value from the middle of the range and both ends of the scale arrive drawn dark. The rate is wrong too: equal steps of data buy wildly unequal steps of colour, fast where two hues meet and slow where one hue runs on, so the ramp invents hard edges in smooth data and flattens real gradients elsewhere. None of it shows up in the usual audit, because the scale is linear, the legend is printed, no bin edge was chosen and no value was touched.
1 exhibit in the gallery
Cherry-picking
The data shown is real. The data missing is the story.
The cherry-picked window
The trend depends on when you press start.
Zoom to the right five years and almost any series can be made to soar, crash, or flatline. The data is untouched — the crop does all the work.
4 exhibits in the gallery
The convenient comparison
We’re #1 — among the competitors we chose.
Any bar looks tall next to the right neighbors. Pick the comparison set after seeing the numbers and “leading the industry” becomes a certainty rather than an achievement.
3 exhibits in the gallery
Survivorship bias
Plotting only the planes that made it home.
If the dataset only contains winners — funds that still exist, companies that went public, planes that returned — every trend tilts rosy. The bullet holes you can see are the ones that didn’t matter.
2 exhibits in the gallery
The ever-rising cumulative
A metric that literally cannot go down.
Plot “cumulative units sold” and the line rises forever, even while the underlying sales collapse. It is the chart equivalent of only counting up.
2 exhibits in the gallery
Regression to the mean
Pick the extremes and they improve without your help.
Almost any measurement is a lasting tendency plus a bit of luck. Sort a group by that measurement and you sort partly on the luck — so the group you picked is more extreme than it really is, and its next reading drifts back toward the average all by itself. Chart the drift and it looks like a treatment working, a trend arriving, or a curse falling.
1 exhibit in the gallery
The self-selected sample
Ten thousand replies, every one of them from somebody who felt like replying.
Some samples are drawn and some samples walk in. When the respondents chose themselves — wrote in, clicked through, left a review, answered the pop-up — what you have is not a slice of the population but a slice of the people moved to reply, and what moves a person to reply is usually the very thing being measured. That makes the bias directional and unbounded, and it means more data cannot fix it: ten thousand volunteers is ten thousand draws from the wrong population. It is the near neighbour of survivorship bias without being the same thing — survivorship is about the cases that dropped out before you looked, self-selection about the ones that stepped forward.
1 exhibit in the gallery
The filter that invents a trade-off
Two things that go together, sliced until they look like a choice.
Some things are worth holding constant and some things are made of the very quantities you are comparing. Price is made of size and quality; getting hired is made of experience and interviewing well; reaching significance is made of sample size and effect size. Slice a dataset by one of those and you have not controlled for anything — you have required the parts to compensate for each other, because the only way into the slice with less of one is more of the other. The two then appear to trade off inside the slice however unrelated, or however positively related, they are outside it. Nothing is exaggerated, nothing is omitted from the chart, and the correlation is computed correctly. The finding is simply about the entry rule rather than about the world.
1 exhibit in the gallery
The late denominator
Start counting at step three and everybody who failed at step two leaves the fraction.
Every rate is a fraction, and a fraction has a top as well as a bottom: somewhere in the process, counting begins. Move that starting line further down the pipeline, past a gate some cases fail to clear, and those cases leave the numerator and the denominator together — so the rate rises without a single outcome improving. Nothing is hidden and nobody is deleted, which is what sets it apart from survivorship bias: survivorship takes the cases out of the dataset, while a late denominator leaves them in it and takes them out only of the fraction, usually a table away, counted and named. They have simply stopped being counted as attempts. The lift is never even, either. It is largest wherever the gate rejects most, which is to say among the cases that were already doing worst, so the same move that raises the headline also flattens the differences the chart was drawn to show.
1 exhibit in the gallery
The size-biased count
A school of forty counts once. So does a school of four thousand.
Every count needs a unit, and a chart of containers gives each container one tally however much it holds. That is the right answer to some questions and the wrong answer to most of the questions people actually ask, because the reader is usually not a school, a class, a bus or a firm — the reader is inside one. Count the contents instead and each container is weighted by its own size, which drags the whole distribution to the right: the big ones, few enough to look like a tail, hold a share of the contents wildly out of proportion to their number. The two averages that result are not rivals and neither is wrong; they differ by exactly the variance divided by the mean, so they agree only when every unit is the same size and diverge fastest where the spread is widest. Nothing is excluded, no axis is bent and the arithmetic is right. The unit is simply not the one the sentence was about.
1 exhibit in the gallery
Framing & context
Technically true, practically misleading.
The missing denominator
More of everything happens in California. More people live there.
Raw counts mostly measure population. Big places top every list — sales, crimes, disease — until you divide by the thing the question is actually about.
2 exhibits in the gallery
The shrinking yardstick
Every year is a record year when the dollar does the climbing.
Plot decades of prices in the dollars of their day and the line can only soar — the measuring unit itself loses value every year, so “all-time high” comes free with the passage of time. A long span of nominal dollars is mostly a chart of inflation wearing the data’s clothes.
2 exhibits in the gallery
Spurious correlation
Margarine consumption and the divorce rate in Maine: a love story.
Comb through enough series and some will move together beautifully by pure chance — or because both quietly follow population, inflation, or time itself. A tight fit on a chart is not a mechanism.
2 exhibits in the gallery
Strategic binning
The map whose color breaks were drawn after the data arrived.
A choropleth’s story lives in its color breaks. Set the bins at 0–10, 10–12, and 12–90 and you can paint the country any shade of crisis you like. Continuous data, discrete lies.
2 exhibits in the gallery
Simpson’s paradox
Every group goes one way. The total goes the other.
Break a comparison into groups and each group can point one way while the pooled total points the other, with no arithmetic error anywhere. It happens when the two sides being compared are not made of the same mix of cases: whichever side was handed the easy ones wins the total on case mix alone. The pooled number then mostly records who got which cases, wearing the clothes of a result.
1 exhibit in the gallery
The redefined measure
The step in the line is the year the definition changed.
Long series outlive the rules that made them. A classification is revised, a diagnostic threshold moves, a question is reworded, an instrument gets more sensitive — and the number jumps on the day the change took effect, with nothing in the world having moved. The chart plots both régimes as one line, so the step reads as an event. It is usually disclosed and almost never on the chart.
1 exhibit in the gallery
Relative risk without the baseline
“Raises your risk 18%.” Of what, from what, by how many?
A percentage increase is a ratio, and a ratio means nothing until you know what it multiplied. Eighteen percent more of a one-in-a-million chance and eighteen percent more of a coin flip are the same number on the page and different worlds to live in. Charts drawn in ratio space — axes labelled “% increased risk”, indexes pinned to 100, bars whose height is a change rather than an amount — cannot show the baseline, because the baseline is not on the axis. The reader supplies it from imagination, and imagination runs high.
1 exhibit in the gallery
The missing base rate
Catches four in five. Wrong seven times in ten. Both are true.
Anything that looks for something — a test, an alarm, a screening rule, a model — produces four outcomes, not one: it fires and the thing is there, it fires and it isn’t, it stays quiet and the thing is there, it stays quiet and it isn’t. A detection rate is built from one column of that table, hits over hits plus misses, and it never counts a single false alarm. So it can be pushed to 100% by firing more often, which makes it a threshold setting rather than a score. How much that costs depends on a number the chart almost never carries: how rare the thing being looked for actually is. Hunt something rare and even a good detector’s alarms are mostly wrong, because there is so much more not-it to be wrong about.
1 exhibit in the gallery
The count that measures the looking
The line rose because the instruments did.
Nothing gets counted until somebody notices it, so every count of detected things is two quantities multiplied: how often the thing happened, and how well anyone was looking. Improve the second — more sensors, more screening, a cheaper test, an easier form, a wider mandate — and the series climbs with no help at all from the first, in exactly the shape a real trend would take. It is the near neighbour of the redefined measure and not the same thing: no definition changed here, no threshold moved, no rulebook was rewritten. The same rule was simply applied by more people, in more places, with better equipment, and the growth in coverage arrives on the page wearing the clothes of growth in the world.
1 exhibit in the gallery
Phantom precision
n = 6, error bars sold separately.
A crisp bar chart looks exactly as confident whether it rests on six million data points or six. Drop the error bars and noise dresses up as signal.
3 exhibits in the gallery
The unfinished period
The last bar is short because the period is young, not because anything changed.
A chart of periods makes a promise so quiet nobody hears it: that each bar is one period, and that the periods are the same length. The last one usually is not. A year drawn at the end of August holds seven months, a month drawn on the third holds two days, and where the figures arrive late even a period that has closed on the calendar is still filling in for weeks afterwards. The bar is drawn at full width regardless, because the width comes from the axis while the height comes from whatever had been counted at the moment somebody pressed download — so the shortfall is a fact about the download date rather than about the world, and it lands in the one position on the chart a reader trusts most, the end, where the story is supposed to be. It is the chart crime with an expiry date. Leave it a few months and it repairs itself, which is exactly why nobody ever goes back to the slide that was already presented. Keep it apart from uneven intervals, which it sits next to: there the unequal bins are known, declared and merely spaced wrongly along the x-axis, so the distortion is in the slope; here the last bin is silently short, nobody has declared anything, and the distortion is in the height.
1 exhibit in the gallery