This is the start of using Chart.js graphing for notebooks with polars as a backend. It gets inspiration from plotly but I like the look of Chart.js graphs more than Plotly plus, supposedly, the canvas based Chartjs should perform better than svg based plotly. Also, I sometimes make small React webapps that natively use Chart.js so I'd like my notebook output to look consistent with those. Lastly, I couldn't get ipychart to work in my environment and it gives an excuse to make a charting library with polars as backend with no pandas.
I struggled with importing the main chart.js plus plugins from a CDN using IPython calls to Javascript for awhile and eventually used vite to publish a bundled version of Chart.js with zoomPlugin and autocolors built in as a single umd.js file. That is here.
With that done, we can run calls to
Javascript(
"""
require(['https://www.unpkg.com/[email protected]/dist/chartBundle.umd.js'], function(chartjs) {
var ctx = document.getElementById("%s");
chartjs.Chart.register(chartjs.zoomPlugin);
new chartjs.Chart(ctx, %s);
})"""
% (this_id, cfg)
)Right now there's a bar function with some options exposed but it already needs some refactoring before more things are added and a thought to the future of making multiple graph types in one.
- Refactor and expose scatter, line charts
- Create functions for generated graphs, ie histograms (bar), ecdf (line), etc
- Expose more chart customizations/options
- Wrap all functions in a class which is registered to pl.DataFrame namespace for
df.cx.scatter(...)syntax. - Publish as pip installable package.
- Expose mixed graphs, (ie lines and bars on same chart)
- Incorporate animation as a dimension similar to plotly
- use mathbox.js for webgl 3d graphs (maybe this is new library)
- connect wasm polars to Python polars to prevent serialization