About This Book
- Create and customize live graphs, by adding style, color, font to make appealing graphs.
- A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits.
- Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more.
Who This Book Is For
This book is for anyone interested in data visualization, to get insights from big data with Python and Matplotlib 2.x. With this book you will be able to extend your knowledge and learn how to use python code in order to visualize your data with Matplotlib. Basic knowledge of Python is expected.
What You Will Learn
- Familiarize with the latest features in Matplotlib 2.x
- Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more.
- Make clear and appealing figures for scientific publications.
- Create interactive charts and animation.
- Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.
- Design intuitive infographics for effective storytelling.
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.
Table of Contents
Chapter 1. Hello Plotting World!
Chapter 2. Figure Aesthetics
Chapter 3. Figure Layout And Annotations
Chapter 4. Visualizing Online Data
Chapter 5. Visualizing Multivariate Data
Chapter 6. Adding Interactivity And Animating Plots
Chapter 7. A Practical Guide To Scientific Plotting
Chapter 8. Exploratory Data Analytics And Infographics