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Hands-On Application Development with PyCharm

You're reading from   Hands-On Application Development with PyCharm Build applications like a pro with the ultimate python development tool

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781837632350
Length 652 pages
Edition 2nd Edition
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Authors (2):
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Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
Bruce M. Van Horn II Bruce M. Van Horn II
Author Profile Icon Bruce M. Van Horn II
Bruce M. Van Horn II
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Table of Contents (24) Chapters Close

Preface 1. Part 1: The Basics of PyCharm
2. Chapter 1: Introduction to PyCharm – the Most Popular IDE for Python FREE CHAPTER 3. Chapter 2: Installing and Configuring PyCharm 4. Part 2: Improving Your Productivity
5. Chapter 3: Customizing Interpreters and Virtual Environments 6. Chapter 4: Editing and Formatting with Ease in PyCharm 7. Chapter 5: Version Control with Git in PyCharm 8. Chapter 6: Seamless Testing, Debugging, and Profiling 9. Part 3: Web Development in PyCharm
10. Chapter 7: Web Development with JavaScript, HTML, and CSS 11. Chapter 8: Building a Dynamic Web Application with Flask 12. Chapter 9: Creating a RESTful API with FastAPI 13. Chapter 10: More Full Stack Frameworks – Django and Pyramid 14. Chapter 11: Understanding Database Management in PyCharm 15. Part 4: Data Science with PyCharm
16. Chapter 12: Turning On Scientific Mode 17. Chapter 13: Dynamic Data Viewing with SciView and Jupyter 18. Chapter 14: Building a Data Pipeline in PyCharm 19. Part 5: Plugins and Conclusion
20. Chapter 15: More Possibilities with Plugins 21. Chapter 16: Your Next Steps with PyCharm 22. Index 23. Other Books You May Enjoy

Viewing and working with data

When you click on the Data tab, you might be a little underwhelmed. As you can see in Figure 13.6, the real action is further down in the debugger window.

Figure 13.6: Nothing shows up in the Data tab until you select one of the sample sets to view as an array

Figure 13.6: Nothing shows up in the Data tab until you select one of the sample sets to view as an array

Shift your attention to the Python Console panel, which appeared at the bottom of the project window when we ran our program in the console. On the right-hand side of the panel, indicated by the arrow, we can see a section that lists all the variables in our program and their respective values. For single variables such as N, this panel is sufficient. However, if you are using NumPy arrays, as we are, viewing the array in the context of a normal debugger window like this one is problematic.

If you click on the View as Array link, which can also be activated by right-clicking the variable, you can see a spreadsheet-like table in the Data panel. Check out Figure 13...

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