Four ways to show shape and spread instead of a single average: histogram, box plot, violin plot and population pyramid. Pick the one that matches how much detail your data, and your reader, actually needs.
A quick look at what's in here. Click through to open any one of them.
These distribution chart templates all answer a question a plain bar chart can't: not just what a dataset's average is, but how the individual values are spread around it, where they bunch up, and whether they form one cluster or several. A histogram, box plot, violin plot and population pyramid all start from the same raw material, a column of numbers, and turn it into a shape. What separates the four is how much of that shape they actually show you, and how much they compress into a few summary statistics you're trusting them to get right.
That trust matters. A tight cluster around 50 and a dataset split evenly between 10 and 90 share the same average, and only a shape-revealing chart tells you which one you're looking at. A histogram shows the shape, but bin width is a setting you choose: pick wrong and one smooth hump can look like three, or a real gap disappears. The box plot skips the shape for five numbers instead (minimum, quartiles, maximum), good for lining up ten groups, but it can't flag a group that's bimodal. A violin plot fixes that: same layout, with the shape drawn in, so two humps show up as two humps.
Population pyramid is the specialist in this family. It's a distribution in the technical sense, age against population count, but it's built for one specific job: comparing that shape between two groups, almost always men and women, back to back around a shared axis. It won't help you spot bimodality in a sales dataset, but it's the standard shape for demographic data and belongs in this category for that reason alone.
Each one opens its own free maker with sample data already loaded.
Test scores, response times, transaction sizes for a single group. A histogram bins the values and draws the actual distribution, gaps, outliers, skew and all, instead of compressing it into a couple of numbers.
Delivery times across ten warehouses, salaries across eight departments. A box plot's five-number summary is compact enough to line up a dozen groups in one row, which a full histogram or violin plot per group can't do without turning into clutter.
Customer spend that might really be two segments, occasional buyers and subscribers, sitting inside one "average." A violin plot draws the full shape next to a box plot's summary, so a second hump shows up instead of getting averaged away.
Population by age and gender, or any count that naturally mirrors around a center line. Population pyramid is built specifically for this back-to-back comparison and reads instantly to anyone who's seen a census chart before.
From a spreadsheet to a published chart, step by step.
One group and you want every detail: histogram. Many groups and you just need spread at a glance: box plot. Many groups and you're worried a box plot's summary hides something: violin plot. Age structure by gender: population pyramid.
Each template linked below opens with sample data already bound in, so you can see the exact column layout: one numeric column for a histogram, a category plus a value column for box and violin plots, before you touch your own data.
Import a CSV or Excel file, paste rows straight from a spreadsheet, or connect a Google Sheet so the chart updates automatically when the source data changes.
For a histogram, check a couple of different bin widths before settling on one, because the shape can change more than you'd expect. Then publish for an interactive embed or export a static PNG, SVG or PDF.
Open the editor and start from any template in this category. Sample data is already loaded.
Open the editorUse a box plot when you're comparing many groups and just need the spread at a glance: it's compact and easy to scan. Switch to a violin plot when you suspect a group's distribution is bimodal or oddly shaped, since a box plot's five-number summary can make two separate clusters look like one smooth range. If you only have two or three groups, a violin plot is almost always worth the extra visual complexity.
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