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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

Data analysis and insights

Remember what we said about the importance of having a question in mind when starting to work on a data science project? This is especially true during this phase, where we explore our dataset and extract insights, which should revolve around our initial question – the connection between typing speed and whether a patient has PD or not.

Throughout this section, we will be working with the EDA.ipynb file, located in the notebooks folder of our current project. In the following subsections, we will be looking at the code included in this notebooks folder. Go ahead and open this Jupyter notebook in your PyCharm editor, or, if you are following our discussions and entering your own code, create a new Jupyter notebook.

Starting the notebook and reading in our processed data

Remember that when you open a Jupyter notebook in Python, you can see the code, but Jupyter won’t run unless you click the Run button. You can see PyCharm ready for this...

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