Book Image

Python GUI programming with Tkinter

By : Alan D. Moore
Book Image

Python GUI programming with Tkinter

By: Alan D. Moore

Overview of this book

Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter. After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell

Chapter 14. Visualizing Data Using the Canvas Widget

With months of experimental data logged in the database, it's time to begin the process of visualizing and interpreting it. Rather than exporting data into a spreadsheet to create charts and graphs, your fellow analysts have asked whether the program itself can create graphical data visualizations. To implement this feature, you're going to need to learn about Tkinter's Canvas widget.

In this chapter, you'll learn the following topics:

  • Using the Canvas widget for drawing and animation
  • Building a simple line graph using Canvas
  • Incorporating more advanced graphs and charts using Matplotlib