PyCharm is one of the most well-known data science tools, offering excellent out-of-the-box support for Python, SQL, and other languages. PyCharm also provides integrations for Databricks, Hugging Face and many other important tools. All these features allow you to write good code and work with your data and projects faster.
PyCharm Professional’s support for Jupyter notebooks combines the interactive nature of Jupyter notebooks with PyCharm’s superior code quality and data-related features. This blog post will explore how PyCharm’s Jupyter support can significantly boost your productivity.
Watch this video to get a comprehensive overview of using Jupyter notebooks in PyCharm and learn how you can speed up your data workflows.
Get acquainted with your data
When you start working on your project, it is extremely important to understand what data you have, including information about the size of your dataset, any problems with it, and its patterns. For this purpose, your …