vega4-extension
A JupyterLab extension for rendering Vega 4 and Vega-Lite 2.
Prerequisites
Usage
To render Vega-Lite output in IPython:
from IPython.display import display
display({
"application/vnd.vegalite.v2+json": {
"$schema": "https://vega.github.io/schema/vega-lite/v2.json",
"description": "A simple bar chart with embedded data.",
"data": {
"values": [
{"a": "A", "b": 28}, {"a": "B", "b": 55}, {"a": "C", "b": 43},
{"a": "D", "b": 91}, {"a": "E", "b": 81}, {"a": "F", "b": 53},
{"a": "G", "b": 19}, {"a": "H", "b": 87}, {"a": "I", "b": 52}
]
},
"mark": "bar",
"encoding": {
"x": {"field": "a", "type": "ordinal"},
"y": {"field": "b", "type": "quantitative"}
}
}
}, raw=True)
Using the Altair library:
import altair as alt
cars = alt.load_dataset('cars')
chart = alt.Chart(cars).mark_point().encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin',
)
chart
Provide Vega-Embed options via metadata:
from IPython.display import display
display({
"application/vnd.vegalite.v2+json": {
"$schema": "https://vega.github.io/schema/vega-lite/v2.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.v2+json": {
"embed_options": {
"actions": False
}
}
}, raw=True)
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
To render a .vl, .vg, vl.json or .vg.json file, simply open it:
Development
See the JupyterLab Contributor Documentation.
