A data visualization generator
that treats a chart as an argument.
Because it is one. Bring a CSV, a spreadsheet or figures buried in a report, and the encoding is chosen for how accurately people read it, the axis stays honest, the labels are sized for a phone, and the finding is written across the top instead of the topic. Free to try, and nothing to install.
Visualise your dataAccurate before pretty
Zero baselines on bars, consistent intervals on time axes, and no perspective on anything. A chart that flatters the number is not a design choice, it is an error with a nice palette.
Readable at the size it will be seen
Most charts are read on a phone. Labels are sized against the frame, not against the desktop preview, and a chart that would need eight tiny labels is summarised to five legible ones instead.
Legible to every reader
Series are separated by more than hue, text clears 4.5:1 against its background, and every figure is real selectable text — so a screen reader gets the numbers rather than the alt attribute’s best guess.
Start to finish
How to generate a data visualization from your figures
- 1
Bring the figures
Upload a CSV, TSV or Excel workbook, paste a table, or hand over a report and let the numbers be pulled out of the prose. No schema to match and no connector to configure.
- 2
Say what you found
Not the topic — the finding. “Growth is concentrated in two regions” produces a different and better sheet than “revenue by region”, because the title and the encoding both follow from it.
- 3
Let the encoding be chosen
The visual encoding follows the ladder below: comparisons that matter go on a common scale, parts of a whole get labelled slices, and anything read by area gets its number written out.
- 4
Check it against the checklist
Unit on the sheet, source named, colour meaning one thing, and a title that states the finding. The checklist further down is the same one used to build it.
- 5
Export it
A PNG for a post or a deck, at up to triple resolution for print; the whole piece as a self-contained HTML file when every shape and string must stay editable; or a share link that is a real page rather than a picture.
When to use this, and when to use a BI tool
Most tools that answer this search are analytics products: they connect to a warehouse, refresh on a schedule and let you drill in. This is not one of them, and pretending otherwise would waste your afternoon. It makes explanatory visuals — the step after the analysis, when you already know what the data says and somebody else needs to see it without opening anything.
| The job | Reach for a BI tool | Reach for this |
|---|---|---|
| Exploring a dataset you have not seen before | A BI or analysis tool. You need to slice, pivot and ask twenty questions before one of them turns into a finding. | Come back once you have the finding. This is the step after that one. |
| A live dashboard wired to a database | A BI tool, without question. Connections, scheduled refreshes and drill-downs are the whole product there. | Not offered. There is no database connector and nothing refreshes on its own. |
| Interactive charts a reader can filter | A dashboard or an embeddable viz tool, if your audience will actually click. | Output is a composed static sheet. Most audiences read and never click, which is the assumption this is built on. |
| Explaining one finding to people who will not open a tool | A BI export is usually a screenshot with a truncated axis and eight-point labels. | This. A designed sheet with the finding as the title, the unit on it and the source named. |
| Something you will put in a report, a post or a deck | Possible anywhere, but you are doing the layout and the restyling yourself each time. | Composed for the shape you pick, in your brand colours, exported as a high-resolution PNG or a web page. |
The one ranking worth memorising
How accurately people read each kind of chart
Visual encodings are not interchangeable. Ordered by how precisely a reader can judge a quantity from each — the higher up the list, the more of the comparison the chart does for them rather than leaving it to their guesswork.
- 1
Position on a common scale
Bars from a shared baseline, dots on one axis
The most accurate judgement people make. If a comparison matters, put it here.
- 2
Position on identical, unaligned scales
Small multiples — the same chart repeated per category
Nearly as good, and it scales to many series without a legend.
- 3
Length
Stacked segments, floating bars
Good, but only for the segment that starts at the baseline. The ones above it are hard.
- 4
Angle and slope
Pie and donut slices, line steepness
Fine for “about a half”, poor for “37% versus 41%”. Label the slices.
- 5
Area
Bubbles, treemaps, area charts
People systematically underestimate area. Doubling a value looks like a 40% rise.
- 6
Colour intensity and saturation
Heatmaps, choropleths
Good for pattern, bad for value. Always pair it with the number written out.
This ordering comes from graphical-perception research into how people judge quantities, and it is why bars beat pies for close comparisons and why bubble charts flatter big values. It is also why the generator reaches for position first.
Six questions to ask the chart before anyone else sees it
- 01Does the title say the finding, not the topic?
- “Revenue grew fastest in the North” beats “Revenue by region”. The title is the only part everyone reads.
- 02Is the unit on the sheet?
- Currency, percentage, per-thousand, and the period. A number without a unit is a decoration.
- 03Can a reader tell what it is not saying?
- A chart of five regions in a company with nine invites a wrong conclusion. Say which are shown.
- 04Does colour mean one thing?
- One hue, one meaning, across the whole sheet — and ideally across the whole report.
- 05Would it survive being screenshotted?
- If the caption carries essential context, that context is lost the first time somebody crops it. Put it on the sheet.
- 06Is the source named?
- Where the numbers came from, and when they were pulled. This is what makes a visualisation citable rather than merely shareable.
Scope and limits
Which visualizations can it generate?
Six: ranked bars, line graphs, donuts, progress meters, comparison tables and timelines. Not histograms, boxplots, heatmaps, scatter plots or maps — those are analysis charts, and the tools ranking beside us on this search do them properly. The six here are the ones that carry a finding to an audience, and each is documented on the chart maker page.
Can I generate a visualization from a CSV or Excel file?
Yes, that is the shortest route in. Upload an .xlsx, .xls, .csv or .tsv up to 25MB and the columns are read directly. From Google Sheets, download as CSV first — there is no live connection to a sheet.
What data can I bring?
A spreadsheet or CSV, a table pasted as text, figures embedded in a report or PDF, or a page of prose with the numbers written into it. There is no required schema.
Can I describe the chart I want in plain English?
Yes. Ask for “that as a line”, “rank it by the second column”, “use our blue”, or “drop everything under two percent”, and the visual is redrawn around the instruction. You can also click into a piece and edit figures and labels directly.
Does it connect to my database or BI tool?
No. It works on data you bring to it — a file, a paste or a document. That keeps the scope honest: this is a tool for making an explanatory visual, not a live dashboard.
Explanatory or exploratory?
Explanatory. It is built for the point at which you already know what the data says and need somebody else to see it. For exploring a dataset for the first time, use an analysis tool and come back when you have a finding.
Is it free?
The free plan needs no card and is exactly one visualization to try, with every chart type and every shape available — enough to run real data through it and decide. The download is standard quality and a small badge sits in the footer. Paid plans go from about 80 pieces a month upward and add brand kits, editing by asking, best-quality downloads and removal of the badge.
How does it handle colour-blind readers?
Series are distinguished by order, label and position as well as hue, text is held to a contrast ratio rather than a swatch, and the default palettes are chosen so adjacent series differ in lightness as well as in colour.
Is the output accessible?
Text in a piece is real text, so it can be selected, searched, translated and read aloud. Charts carry accessible labels, and a share link is a real page rather than an image.
Can I export something editable?
Yes, though not as SVG — there is no SVG export. The editable export is the piece itself as one self-contained HTML file: every heading, label and figure is real text in real markup, so a developer can restyle it, host it or fold it into a page. Inside the editor you can also double-click any label and change it in place before you export anything.
You already found the story
This is the part where somebody else has to see it in three seconds.
Make a visualisation