VedaCanvas

VedaCanvas

Every chart in my visualization notes, built from your own data, with every dial in the open. Publication-grade static figures, an interactive toggle, and the Python that made them, ready to paste into a notebook.

Open a dataset

CSV or Excel. The real pandas, matplotlib, seaborn and plotly run inside your browser (WebAssembly); your file never leaves your machine.

The transaction data

The retail loyalty dataset from my visualization notes, rebuilt: 420 invoices, 23 columns of stores, cities, spend, discounts, memberships and points.

The chart chooser is my own taxonomy. Pick what you are trying to SAY (comparison, relationship, proportion, distribution, trend) or what you HAVE (one continuous column, two categoricals, and so on), and the families that fit appear with the reason they fit. Every chart exports as Python.
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