Labi Plot · Scientific graphing for biologists
Paste your data, let Labi Plot detect the structure, pick a chart type, run your stats, and export a clean figure. No scripting. No setup. Just your results, in a format your PI will actually approve.
What's planned
Paste any data format
Copy from your spreadsheet and paste directly. Labi Plot detects columns, infers group labels from headers, and flags any structure issues before you touch a single setting.
Auto chart detection
Paste two groups and it suggests a violin or box plot. Paste time-series data and it recommends a line chart. You pick — but the right answer is always already highlighted.
Built-in statistics
Select your groups and run. Labi Plot handles the stats backend (Python/SciPy) and puts p-values, effect sizes, and significance brackets directly on your figure. Results attached to the chart, not a separate table.
Export publication-ready
Export at 300 dpi for print, or as editable SVG to touch up in Illustrator. Figure dimensions, font sizes, and axis labels follow journal guidelines by default. One click to a figure your co-authors can actually use.
How it works
Copy from Excel, Google Sheets, or any text editor. Labi Plot auto-detects column structure, group labels, and data types — no configuration required.
Violin, box, dot plot, bar chart, scatter, or line. The recommended type is highlighted based on your data shape — pick it or override it.
Select the test — t-test, one-way ANOVA, curve fitting — and Labi Plot runs it server-side with SciPy. P-values and significance brackets appear directly on the chart.
Adjust colours, labels, and axis ranges. Export as SVG, PNG at 300 dpi, or PDF — sized for the journal you're targeting. Done.
Data input
Built for scientists in
Early access
Labi Plot is in active development — Flutter frontend, Python/SciPy backend. Drop your email and we'll reach out when the beta opens.
No spam. One email when the beta is ready.