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Hands-On Application Development with PyCharm

You're reading from   Hands-On Application Development with PyCharm Accelerate your Python applications using practical coding techniques in PyCharm

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Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781789348262
Length 494 pages
Edition 1st Edition
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Author (1):
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Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
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Table of Contents (23) Chapters Close

Preface 1. Section 1: The Basics of PyCharm
2. Introduction to PyCharm - the Most Popular IDE for Python FREE CHAPTER 3. Installing and Configuring PyCharm 4. Section 2: Improving Your Productivity
5. Customizing Interpreters and Virtual Environments 6. Editing and Formatting with Ease in PyCharm 7. Version Control with Git in PyCharm 8. Seamless Testing, Debugging, and Profiling 9. Section 3: Web Development in PyCharm
10. Web Development with JavaScript, HTML, and CSS 11. Integrating Django in PyCharm 12. Understanding Database Management with PyCharm 13. Building a Web Application in PyCharm 14. Section 4: Data Science with PyCharm
15. Turning on Scientific Mode 16. Dynamic Data Viewing with SciView and Jupyter 17. Building a Data Pipeline in PyCharm 18. Section 5: Plugins and Conclusion
19. More Possibilities with PyCharm Plugins 20. Future Developments 21. Assessments 22. Other Books You May Enjoy

Chapter 13

  1. To collect a dataset, you can do any of the following:
  • Download it from an external source
  • Manually collect it or use web scraping
  • Collect it via a third party
  • Work with a database
  1. Git LFS can work seamlessly with Git. Specifically, we can use Git LFS to track the extensions of large files that we want to have version control on, and Git will work with Git LFS to delegate those files when we want to push our projects to GitHub. Afterward, we simply need to use Git in the usual way.
  2. An attribute that contains continuous, numerical data often has its missing values filled out with the mean. On the other hand, attributes with discrete numerical data as well as categorical data can use the mode to fill out their missing values.
  3. In a naive encoding scheme, you may inadvertently apply some sort of an ordered relation to the data when the original data is replaced with...
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