Heatmap generator
Upload a data matrix and get a clean, clustered heatmap — correlation matrices, gene-expression maps, and more — rendered with matplotlib/seaborn and exportable for journals.
Why use it
Clustering done right
Add hierarchical row/column clustering, dendrograms, and z-score normalization without writing any seaborn code.
Real plotting engine
MindPlot writes and runs actual matplotlib/seaborn code, so your heatmap is reproducible and styled to journal standards, not a screenshot.
Export for submission
Download editable SVG or high-DPI PDF/PNG/EPS that meets figure requirements.
How it works
Upload your matrix
Drop in a CSV of values — a correlation matrix, an expression table, or any numeric grid.
Describe the heatmap
Ask for clustering, a colour scale, normalization, or annotations in plain language.
Export the figure
Download a publication-ready SVG/PDF, or refine the palette and labels first.
What you can do with it
Gene-expression heatmaps
Show expression across samples with clustered rows and columns.
Correlation matrices
Visualize pairwise correlations across many variables at a glance.
Confusion matrices
Present classifier performance as a clean, labelled grid.
Frequently asked questions
What data do I need for a heatmap?
A numeric matrix in CSV form — for example a gene-by-sample expression table or a correlation matrix. Row and column labels are used automatically.
Can I add clustering?
Yes — add hierarchical clustering with dendrograms on rows, columns, or both, plus z-score normalization.
Is the figure publication-ready?
Yes — it is rendered with matplotlib/seaborn using journal-grade styling and exports editable SVG and high-DPI PDF/PNG/EPS.
Do I need to code?
No — describe the heatmap in plain language and MindPlot writes and runs the plotting code for you.
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