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Hands-On Application Development with PyCharm

Hands-On Application Development with PyCharm

By : Bruce M. Van Horn II, Quan Nguyen
4.8 (4)
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Hands-On Application Development with PyCharm

Hands-On Application Development with PyCharm

4.8 (4)
By: Bruce M. Van Horn II, Quan Nguyen

Overview of this book

In the quest to develop robust, professional-grade software with Python and meet tight deadlines, it’s crucial to have the best tools at your disposal. In this second edition of Hands-on Application Development with PyCharm, you’ll learn tips and tricks to work at a speed and proficiency previously reserved only for elite developers. To achieve that, you’ll be introduced to PyCharm, the premiere professional integrated development environment for Python programmers among the myriad of IDEs available. Regardless of how Python is utilized, whether for general automation scripting, utility creation, web applications, data analytics, machine learning, or business applications, PyCharm offers tooling that simplifies complex tasks and streamlines common ones. In this book, you'll find everything you need to harness PyCharm's full potential and make the most of Pycharm's productivity shortcuts. The book comprehensively covers topics ranging from installation and customization to web development, database management, and data analysis pipeline development helping you become proficient in Python application development in diverse domains. By the end of this book, you’ll have discovered the remarkable capabilities of PyCharm and how you can achieve a new level of capability and productivity.
Table of Contents (24 chapters)
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1
Part 1: The Basics of PyCharm
4
Part 2: Improving Your Productivity
9
Part 3: Web Development in PyCharm
15
Part 4: Data Science with PyCharm
19
Part 5: Plugins and Conclusion

Starting with a question

Everything in science starts with a question. For our purposes, we’ll consider two possible scenarios:

  • We have a specific question in mind and we need to collect and analyze appropriate data to answer that question
  • We already have data, and during exploration, a question has arisen

In our case, we’re going to recreate the data analysis phase of a potentially important breakthrough in the field of medical diagnosis. I’ll be presenting an example from Kaggle taken from a paper titled High-accuracy detection of early Parkinson’s Disease using multiple characteristics of finger movement while typing, which was conducted by Warwick Adams in 2017. You’ll find the full study paper and the dataset links in the Further reading section of this chapter.

Note

Kaggle is an online data community designed for data scientists and ML engineers. The site provides competitions, datasets, playgrounds, and other educational...

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