Data Visualization
A chart can communicate a pattern in seconds that a table of numbers cannot. This module introduces the principles of effective data visualization and teaches two of the most widely used Python visualization libraries: Matplotlib for publication-quality static plots, and Plotly for interactive charts.
The emphasis throughout is on choosing the right chart type for the data and the question — and on making charts readable and informative rather than decorative.
Lessons
- Introduction to Data Visualization — Why visualization matters, the major chart types and when to use each, and principles of clear visual communication.
- Visualizing Data with Matplotlib — Line charts, bar charts, scatter plots, and histograms; customizing labels, colors, and layouts; saving figures.
- Visualizing Data with Plotly — Building interactive charts with Plotly Express; hover information, zooming, and producing dashboard-ready visualizations.
- Module Assessment — A visualization assessment requiring you to choose appropriate chart types and produce clear, correctly labeled figures for a given dataset.