Dive into the fourth part of a comprehensive data visualization course focusing on Altair scales, axes, and legends in Python. Learn to leverage Vega's rich features for customizing data visualizations. Explore the Antibiotics dataset while mastering techniques to adjust scales (linear, log, sqrt) and create nonlinear axes. Discover how to customize axes with sorting and orientation options, equalize axes with matching domains, and adjust grid lines. Gain expertise in customizing color legends, including domain and range parameters, position, and orientation. Explore Altair color schemes and learn to extract substrings as new features using transform_calculate. Uncover biological clues from visualizations, use colors to encode quantitative values, and sort axes with EncodingSortField. Master the art of customizing color legends and titles to create polished, informative data visualizations.
Overview
Syllabus
Role of Scales, Axis, Legends in Data Visualization
The Antibiotics dataset
Adjusting Scales linear, log, sqrt in Altair
Nonlinear axes scales
Customizing axis with sort='descending' and axis orientation
Equalizing the axes with matching domains
Adjusting grid lines with grid=False and tickCount
Customize color legends w/ domain and range params
Legend position & orientation
Altair color schemes
Extract substring as new feature using transform_calculate
Extracting biological clues from visualization
Using colors to encode quantitative values
Sorting axis with EncodingSortField
Customizing color legends
Customizing title with configure_title
Taught by
Samuel Chan
