Altair -

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

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

Install Altair using pip . It is highly recommended to work within a Jupyter notebook environment (JupyterLab, VS Code, Colab) for automatic rendering. altair

You can save your chart as a JSON file (Vega-Lite spec) or render it as an image/HTML file. chart.save('chart.html') Use code with caution. Copied to clipboard Choose the chart type (e

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. It is highly recommended to work within a

Map data columns to visual properties (e.g., .encode(x='column1', y='column2') ). Example: Simple Bar Chart

# Create a bar chart with the average of column 'b' alt.Chart(data).mark_bar().encode( x='a', y='mean(b)' # Aggregation ) Use code with caution. Copied to clipboard 4. Customizing Your Visualization