Altair: Declarative Visualization for Python

Overview Altair is a statistical visualization library for Python, based on Vega-Lite. It is "Declarative", meaning you describe what you want the chart to look like (mapping columns to visual channels), not how to draw lines and pixels.

The Grammar of Graphics You map data columns to channels:

• x / y: Position.
• color: Color.
• size: Size.
• shape: Shape.

Example

import altair as alt
from vega_datasets import data

cars = data.cars()

chart = alt.Chart(cars).mark_circle().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
    tooltip=['Name', 'Origin']
).interactive()

Pros

• Consistent API: Once you learn the grammar, you can build any chart.
• Interactivity: Zoom/Pan/Tooltip is one line (.interactive()).
• JSON: The output is a JSON spec (Vega-Lite), which can be easily embedded in websites.

Cons

• Large Data: Since it embeds the data into the JSON, plotting >5,000 points can crash the browser. (Workarounds exist using Altair Saver or VegaFusion).