Python Data Visualization: Matplotlib & Seaborn Masterclass
Bring your data to LIFE and master Python’s most popular data analytics & visualization libraries: Matplotlib & Seaborn
Created by Maven Analytics, Chris Bruehl | 7.5 hours of video course
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data visualization: Matplotlib & Seaborn. We’ll start with a quick introduction to data visualization frameworks and best practices, and review essential visuals, common errors, and tips for effective communication and storytelling.
From there we’ll dive into Matplotlib fundamentals, and practice building and customizing line charts, bar charts, pies & donuts, scatterplots, histograms and more. We’ll break down the components of a Matplotlib figure and introduce common chart formatting techniques, then explore advanced customization options like subplots, GridSpec, style sheets and parameters.
Finally we’ll introduce Python’s Seaborn library. We’ll start by building some basic charts, then dive into more advanced visuals like box & violin plots, PairPlots, heat maps, FacetGrids, and more.
What you’ll learn
- Master the essentials of Matplotlib & Seaborn, two of Python’s most powerful data visualization packages
- Design and format 20+ chart types using Matplotlib & Seaborn, including line charts, bar charts, scatter plots, histograms, violin plots, heatmaps and more
- Learn advanced customization options like subplots, gridspec, style sheets and parameters
- Apply best practices for data visualization, storytelling, formatting and visual design
- Build powerful, practical skills for modern analytics and business intelligence
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