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Raspberry Pi 3 Cookbook for Python Programmers

Raspberry Pi 3 Cookbook for Python Programmers

By : Steven Lawrence Fernandes, Tim Cox
3.8 (10)
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Raspberry Pi 3 Cookbook for Python Programmers

Raspberry Pi 3 Cookbook for Python Programmers

3.8 (10)
By: Steven Lawrence Fernandes, Tim Cox

Overview of this book

Raspberry Pi 3 Cookbook for Python Programmers – Third Edition begins by guiding you through setting up Raspberry Pi 3, performing tasks using Python 3.6, and introducing the first steps to interface with electronics. As you work through each chapter, you will build your skills and apply them as you progress. You will learn how to build text classifiers, predict sentiments in words, develop applications using the popular Tkinter library, and create games by controlling graphics on your screen. You will harness the power of a built in graphics processor using Pi3D to generate your own high-quality 3D graphics and environments. You will understand how to connect Raspberry Pi’s hardware pins directly to control electronics, from switching on LEDs and responding to push buttons to driving motors and servos. Get to grips with monitoring sensors to gather real-life data, using it to control other devices, and viewing the results over the internet. You will apply what you have learned by creating your own Pi-Rover or Pi-Hexipod robots. You will also learn about sentiment analysis, face recognition techniques, and building neural network modules for optical character recognition. Finally, you will learn to build movie recommendations system on Raspberry Pi 3.
Table of Contents (17 chapters)
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Logging and plotting data


Now that we are able to sample and collect a lot of data, it is important that we can capture and analyze it. For this, we will make use of a Python library called matplotlib, which includes lots of useful tools for manipulating, graphing, and analyzing data. We will use pyplot (which is a part of matplotlib) to produce graphs of our captured data. For more information on pyplot, go to http://matplotlib.org/users/pyplot_tutorial.html.

It is a MATLAB-style data visualization framework for Python.

Getting ready

To use pyplot, we will need to install matplotlib.

Note

Because of a problem with the matplotlib installer, performing the installation using pip-3.2 doesn't always work correctly. The method that follows will overcome this problem by performing all the steps pip does manually; however, this can take over 30 minutes to complete. To save time, you can try the pip installation, which is much quicker. If it doesn't work, you can install it using the aforementioned...

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