This is the code repository for Python Data Visualization with Matplotlib 2.x [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers a simple but powerful plotting interface, versatile plot types, and robust customization. Python Data Visualization with Matplotlib 2.x illustrates the methods and applications of various plot types through real-world examples. It begins by giving the viewers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which supply insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this course, you will be well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high-quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshape your message crisply understandable.
- Master 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 animations.
- 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.
To fully benefit from the coverage included in this course, you will need:
Basic knowledge of Python is required
This course has the following software requirements:
Python 3.x
Matplotlib 2.x