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Matplotlib 2.x By Example

Matplotlib 2.x By Example

By : Allen Yu, Claire Chung, Aldrin Yim
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Matplotlib 2.x By Example

Matplotlib 2.x By Example

By: Allen Yu, Claire Chung, Aldrin Yim

Overview of this book

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. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers 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 give 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 book, you will become 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 reshaping your message crisply understandable.
Table of Contents (9 chapters)
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Hello Plotting World!

To learn programming, we often start with printing the "Hello world!" message. For graphical plots that contain all the elements from data, axes, labels, lines and ticks, how should we begin?

This chapter gives an overview of Matplotlib's functionalities and latest features. We will guide you through the setup of the Matplotlib plotting environment. You will learn to create a simple line graph, view, and save your figures. By the end of this chapter, you will be confident enough to start building your own plots, and be ready to learn about customization and more advanced techniques in the coming sections.

Come and say "Hello!" to the world of plots!

Here is a list of topics covered in this chapter:

  • What is Matplotlib?
  • Setting up the Python environment
  • Installing Matplotlib and its dependencies
  • Setting up the Jupyter notebook
  • Plotting the first simple line graph
  • Loading data into Matplotlib
  • Exporting the figure

  

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