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Data Science · Ebook

Matplotlib: Visualizing Data in Python

by Shriira Press

4.7(8,812)89 pagesPublished 2026

A comprehensive, self-contained guide to Matplotlib, the foundational plotting library of the Python scientific and data ecosystem — the tool that turns arrays of numbers into figures you can see, reason about, and publish. Nearly every chart in a Python data-science or machine-learning workflow is drawn by Matplotlib (directly, or through libraries built on it). This book teaches it from first principles: the Figure/Axes architecture and the two APIs, the full catalog of plot types, customization and layout, images and colormaps, themes, 3D and animation, the ecosystem (seaborn and friends), and the craft of making figures that are clear, honest, and publication-ready. It blends intuition, the concepts behind the API, and runnable code.

Contents

  1. 1Preface
  2. 2Chapter 1 — What Is Matplotlib?
  3. 3Chapter 2 — The Anatomy of a Figure: Figure, Axes, and the Two APIs
  4. 4Chapter 3 — Your First Plots: Line, Scatter, and Bar
  5. 5Chapter 4 — Statistical and Distribution Plots
  6. 6Chapter 5 — Plotting from Data: NumPy and pandas
  7. 7Chapter 6 — Images, Colormaps, and Heatmaps
  8. 8Chapter 7 — Styling Plots: Colors, Lines, Markers, and Text
  9. 9Chapter 8 — Axes, Scales, Ticks, and Dates
  10. 10Chapter 9 — Subplots and Layout
  11. 11Chapter 10 — Themes, Styles, and rcParams
  12. 12Chapter 11 — 3D, Animation, and Interactivity
  13. 13Chapter 12 — The Ecosystem: seaborn, pandas, and beyond
  14. 14Chapter 13 — Publication, Production, and Best Practices
  15. 15Appendix A — Glossary and API Quick Reference
  16. 16Appendix B — Further Reading and Resources