Matplotlib 2.x By Example

This is the code repository for Matplotlib 2.x By Example, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the 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.

Instructions and Navigation

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.

The code will look like the following:

evens = []
with open as f:
    for line in f.readlines():
        evens.append(line.split()[1])

These are the prerequisites for this book:

Basic Python knowledge is expected. Interested readers can refer to Learning Python by Fabrizio Romano if they are relatively new to Python programming.
A working installation of Python 3.4 or later is required. The default Python distribution can be obtained from https://www.python.org/download/. Readers may also explore other Python distributions, such as Anaconda (https://www.continuum.io/downloads), which provides better package dependency management.
A Windows 7+, macOS 10.10+, or Linux-based computer with 4 GB RAM or above is recommended.
The code examples are based on Matplotlib 2.x, Seaborn 0.8.0, Pandas 0.20.3, Numpy 1.13.1, SciPy 0.19.1, pycountry 17.5.14, stockstats 0.2.0, BeautifulSoup4 4.6.0, requests 2.18.4, plotly 2.0.14, scikit-learn 0.19.0, GeoPandas 0.2.1, PIL 1.1.6, and lifelines 0.11.1. Brief instructions for installing these packages are included in the chapters, but readers can refer to the official documentation pages for more details.

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