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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

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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