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Python GUI Programming - A Complete Reference Guide

You're reading from   Python GUI Programming - A Complete Reference Guide Develop responsive and powerful GUI applications with PyQt and Tkinter

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Product type Course
Published in Jun 2019
Publisher Packt
ISBN-13 9781838988470
Length 746 pages
Edition 1st Edition
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Authors (2):
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B. M. Harwani B. M. Harwani
Author Profile Icon B. M. Harwani
B. M. Harwani
Alan D. Moore Alan D. Moore
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Alan D. Moore
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Table of Contents (28) Chapters Close

Title Page
Copyright About Packt Contributors Preface 1. Introduction to Tkinter FREE CHAPTER 2. Designing GUI Applications with Tkinter 3. Creating Basic Forms with Tkinter and ttk Widgets 4. Reducing User Error with Validation and Automation 5. Planning for the Expansion of Our Application 6. Creating Menus with Menu and Tkinter Dialogs 7. Navigating Records with Treeview 8. Improving the Look with Styles and Themes 9. Creating Automated Tests with unittest 10. Improving Data Storage with SQL 11. Connecting to the Cloud 12. Visualizing Data Using the Canvas Widget 13. Creating a User Interface with Qt Components 14. Event Handling - Signals and Slots 15. Understanding OOP Concepts 16. Understanding Dialogs 17. Understanding Layouts 18. Networking and Managing Large Documents 19. Database Handling 20. Using Graphics 21. Implementing Animation 22. Using Google Maps 1. Other Books You May Enjoy

Advanced graphs using Matplotlib and Tkinter

Our line graph is pretty, but it still needs considerable work to be fully functional: it lacks a scale, grid lines, and other features that would make it a completely useful chart.

We could spend a lot of time making it more complete, but there's a faster way to get much more satisfactory graphs and charts in our Tkinter application: Matplotlib.

Matplotlib is a third-party library for generating professional-quality, interactive graphs of all types. It's a vast library with many add-ons, and we won't cover much of its actual usage, but we should look at how to integrate Matplotlib into a Tkinter application. To do this, we'll create a bubble chart showing the yield of each plot as it relates to humidity and temperature.

You should be able to install matplotlib using pip with the command pip install --user matplotlib...
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