Datawrapper

Datawrapper is a browser-based tool for making charts, maps and tables that go on the web. You paste or upload your data, pick a chart type, adjust labels and colors, and publish. You get an embed code for a responsive chart that works on phones, plus an image if you need one. Newsrooms use it heavily, and that shows in the defaults: tidy typography, sensible colors, readable labels and very little clutter.

It does one thing, a single publishable chart, and does it quickly. The free plan covers most of what a writer, researcher or small team needs.

Who it suits

Datawrapper suits people who publish charts more than they analyze data: journalists, communications teams, researchers writing a report, bloggers, nonprofit staff turning a survey into something people will read. If you already know what the chart should say and need it on a page within the hour, this is the tool.

It suits analysts less, because it has no real way to explore data or calculate inside the tool. Do the analysis elsewhere, in a spreadsheet, SQL or Python, then bring the final table to Datawrapper.

What it does well

The defaults are good enough to publish. A bar chart comes out with direct value labels, light gridlines and a clean font, and the layout adapts to narrow screens without extra work. That saves the time most tools spend on removing decoration.

Other strengths:

• Annotations and highlights: you can color one bar, add a text note to a line chart, or mark a range, all from the editor.
• Maps: choropleth and symbol maps with many ready-made base maps, from countries to regions and districts.
• Tables: sortable, searchable tables with sparklines, heatmap cells and bar cells, which is more than most chart tools offer.
• Accessibility: you can write an alternative description for screen readers, and the colorblind check previews how the palette looks to people with color vision deficiencies. The accessible charts guide covers what else to do.
• Updating: a chart can be linked to an external data source, such as a published Google Sheet, so it refreshes without republishing.

Where it gets in the way

The chart types are a fixed list. They cover the common cases well (bars, lines, areas, scatter plots, dot plots, range plots, donuts, maps and tables), but anything outside the list is out of reach. Network graphs and unusual custom layouts need another tool.

There is no data modeling. Datawrapper expects a clean table in the shape the chart needs. If your data is in long format and the chart needs wide, reshape it first.

Interactivity is limited to tooltips, some toggles and the chart itself. There are no linked dashboards and no filters that control several charts at once.

Free options

The free plan lets you create unlimited charts, maps and tables, publish and embed them, and download them as PNG images. Published charts carry a "Created with Datawrapper" credit that you must keep. Paid plans add vector exports (SVG and PDF), custom themes with your own fonts and colors, removal of the credit, extra chart types, and team and security features.

How it compares

Against Flourish: both are browser tools for published charts. Datawrapper is quicker for standard, static-looking charts and maps with excellent defaults. Flourish has more templates, animation and story formats, at the cost of more settings to work through. A common split is Datawrapper for the everyday chart and Flourish for the showpiece.

Against Tableau: Tableau is for exploring data and building dashboards. Datawrapper is for the final chart in an article or report. Many people use both, finding the story in one and publishing it in the other.

A good first project

Take a small table you already have, such as monthly website visits by channel, or a survey question with five answer options. Make it a sorted bar chart in Datawrapper, write the takeaway as the title ("Search brings in half of all visits"), highlight the one bar the title talks about, and add a source line.

Then switch the chart type to a line chart or a dot plot and see what changes. Datawrapper makes trying alternatives cheap, which is a good way to learn how to choose a chart.