Python data to an interactive chart

A Python list of dictionaries becomes a JavaScript array of objects. This example passes per-species statistics from the Palmer Penguins dataset to the browser, where an Observable input chooses the plotted metric. The switch recomputes entirely in the browser. Python is not involved after the initial render.

import observablejs as obs

species_stats = [
    {"species": "Adelie", "count": 152, "mean_mass_g": 3701},
    {"species": "Chinstrap", "count": 68, "mean_mass_g": 3733},
    {"species": "Gentoo", "count": 124, "mean_mass_g": 5076},
]

notebook = obs.Notebook(
    obs.js(
        """
        const metric = view(Inputs.select(
          new Map([
            ["Penguin count", "count"],
            ["Mean body mass (g)", "mean_mass_g"]
          ]),
          {label: "Metric"}
        ));
        """,
        key="metric_control",
    ),
    obs.js(
        """
        Plot.barX(speciesStats, {
          x: metric,
          y: "species",
          fill: "species",
          tip: {
            // This example references a theme variable used by mdx-marimo.
            // Replace it with a CSS color or remove `fill` in another host.
            fill: "var(--marimo-island-background)"
          }
        }).plot({
          height: 240,
          marginLeft: 76,
          color: {legend: true},
          x: {grid: true, label: metric === "count" ? "Penguins" : "Body mass (g)"},
          y: {label: null}
        })
        """,
        key="chart",
    ),
    variables={"speciesStats": species_stats},
)

full_view = notebook.view()
full_view

Data crosses once

The variables mapping publishes the Python list under the JavaScript name speciesStats. The chart cell reads it like any graph variable.
view(Inputs.select(...)) defines metric in the browser. Changing it invalidates only the chart cell.
A pandas or Polars DataFrame works in place of the literal list. It arrives as the same array of row objects. See Variables and serialization.

Update or scale the data path

Update the records after render with notebook.update_variables({"speciesStats": ...}). The chart recomputes while the input keeps its selection. See Python to Observable.
For large tables, register a file with files= and load it in the browser with FileAttachment(...).csv().

Data crosses once​

Update or scale the data path​

Data crosses once

Update or scale the data path