Altair works best with tidy data—long-form data where each row is an observation and each column is a variable.
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. altair
import altair as alt import pandas as pd # 1. Data data = pd.DataFrame({'a': ['A', 'B', 'C'], 'b': [28, 55, 43]}) # 2. & 3. Chart + Mark + Encoding chart = alt.Chart(data).mark_bar().encode( x='a', y='b' ) # Display (if in notebook) # chart.show() Use code with caution. Copied to clipboard 3. Data Transformation & Aggregation Altair works best with tidy data—long-form data where
Install Altair using pip . It is highly recommended to work within a Jupyter notebook environment (JupyterLab, VS Code, Colab) for automatic rendering. import altair as alt import pandas as pd # 1
# 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
Use chart.validate() to check for invalid specifications.