Altair Today

Choose the chart type (e.g., mark_point() , mark_bar() , mark_line() ).

alt.Chart(data).mark_bar().encode( x=alt.X('a', title='Category'), y=alt.Y('b', title='Value'), color='a' # Color by category ).properties( title='My First Altair Chart', width=400, height=300 ) Use code with caution. Copied to clipboard 5. Interaction

Learn how to (e.g., lines and points)?

You can refine your plot by adding titles, changing colors, and adjusting axes using .properties() and alt.Axis() .

Use chart.validate() to check for invalid specifications. altair

Altair is a declarative statistical visualization library for Python, built on the powerful Vega and Vega-Lite grammar. It allows you to create interactive, informative charts using a consistent API, where you describe the links between data columns and visual encoding channels (like x-axis, y-axis, color, size) rather than explicitly coding drawing commands.

One of Altair's strongest features is the ability to create interactivity (like panning, zooming, and tooltips) by linking chart components. Choose the chart type (e

Altair works best with tidy data—long-form data where each row is an observation and each column is a variable.