Learn how to create clear, accurate, and effective data visualizations using Python. Participants will explore key principles of visualization design, including how to choose appropriate chart types, use color effectively, and avoid common plotting mistakes involving scales, axes, ordering, labels, and other design choices. The session will also introduce three widely used Python visualization libraries, (Matplotlib, Seaborn, Plotly), and discuss their strengths, differences, and appropriate use cases. Guided demonstrations and hands-on exercises will give participants experience creating and improving visualizations with each library.
Learning outcomes:
- Principles of effective data visualization
- Choosing appropriate chart types for different types of data
- Using color effectively and avoiding misleading color choices
- Recognizing and correcting common visualization mistakes
- Comparing Matplotlib, Seaborn, and Plotly and when to use each
- Creating visualizations in Python with Matplotlib
- Creating statistical visualizations with Seaborn
- Creating interactive visualizations with Plotly
Presented by Satyar Foroughi
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