vega5-extension

A JupyterLab extension for rendering Vega 5 and Vega-Lite 3.

This extension is in the official JupyterLab distribution.

Usage

To render Vega-Lite output in IPython:

from IPython.display import display

display(
    {
        "application/vnd.vegalite.v3+json": {
            "$schema": "https://vega.github.io/schema/vega-lite/v3.json",
            "description": "A simple bar chart with embedded data.",
            "data": {
                "values": [
                    {"a": "A", "b": 28},
                    {"a": "B", "b": 55},
                    {"a": "C", "b": 43},
                    {"a": "D", "b": 91},
                    {"a": "E", "b": 81},
                    {"a": "F", "b": 53},
                    {"a": "G", "b": 19},
                    {"a": "H", "b": 87},
                    {"a": "I", "b": 52},
                ]
            },
            "mark": "bar",
            "encoding": {
                "x": {"field": "a", "type": "ordinal"},
                "y": {"field": "b", "type": "quantitative"},
            },
        }
    },
    raw=True,
)
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Using the Altair library:

import altair as alt

cars = alt.load_dataset("cars")

chart = (
    alt.Chart(cars)
    .mark_point()
    .encode(
        x="Horsepower",
        y="Miles_per_Gallon",
        color="Origin",
    )
)

chart
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Provide Vega-Embed options via metadata:

from IPython.display import display

display(
    {
        "application/vnd.vegalite.v3+json": {
            "$schema": "https://vega.github.io/schema/vega-lite/v3.json",
            "description": "A simple bar chart with embedded data.",
            "data": {
                "values": [
                    {"a": "A", "b": 28},
                    {"a": "B", "b": 55},
                    {"a": "C", "b": 43},
                    {"a": "D", "b": 91},
                    {"a": "E", "b": 81},
                    {"a": "F", "b": 53},
                    {"a": "G", "b": 19},
                    {"a": "H", "b": 87},
                    {"a": "I", "b": 52},
                ]
            },
            "mark": "bar",
            "encoding": {
                "x": {"field": "a", "type": "ordinal"},
                "y": {"field": "b", "type": "quantitative"},
            },
        }
    },
    metadata={"application/vnd.vegalite.v3+json": {"embed_options": {"actions": False}}},
    raw=True,
)
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Provide Vega-Embed options via Altair:

import altair as alt

alt.renderers.enable("default", embed_options={"actions": False})

cars = alt.load_dataset("cars")

chart = (
    alt.Chart(cars)
    .mark_point()
    .encode(
        x="Horsepower",
        y="Miles_per_Gallon",
        color="Origin",
    )
)

chart
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To render a .vl, .vg, vl.json or .vg.json file, simply open it:

Development

See the JupyterLab Contributor Documentation.