Grammar-of-graphics charts,
native to Mojo

One fluent Plot builder – mark, encode, theme – covers 40+ chart types,
rendered to SVG or raster.

Quickstart Browse examples

See it before you build it

Every chart below comes straight from the example gallery.

Nine of the 40+ chart types this package builds -- see the rest, source next to rendered output, in the examples gallery.

Why dataviz_mojo?

Grammar of graphics when you want it

One fluent Plot builder – mark_point()/mark_bar()/… + encode() + .theme() is enough to build any chart.

40+ convenience chart functions

Scatter and bar through sankey, treemap, radar, and candlestick – statistical, financial, hierarchical, radial, and network charts all share the same API.

Native Mojo, no bindings

Pure Mojo top to bottom, built on canvas_mojo!

SVG or raster

Every Plot renders to crisp SVG or a PNG/BMP raster canvas – save() picks the backend from the file extension.

One pixi install away

A git-source pixi dependency – pixi install builds dataviz_mojo and canvas_mojo for you

Open Source

MIT licensed on GitHub – read the source, file an issue, or send a PR.

A first chart

from dataviz_mojo import Plot, save

def main() raises:
    var x: List[Float64] = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
    var y: List[Float64] = [2.3, 4.1, 3.6, 5.8, 5.1, 7.4, 6.9, 8.2, 9.0, 8.6]

    var plot = (
                Plot()
                .mark_point()
                .encode(x=x, y=y)
               )

    save(plot, "chart.svg")

That’s the same pattern behind every mark type this package supports, plus color/size encoding, facets, multi-series layering, and the raster backend.

Quickstart →

Grammar-of-graphics charts, native to Mojo