PyCharm

Read this article to learn the difference between vanilla Jupyter notebooks and Jupyter Notebook support in PyCharm, a professional data science IDE.

Discover seven ways you can use Jupyter notebooks in PyCharm to explore and work with your data more quickly and effectively.

Read this guide to learn how to use Jupyter notebooks in PyCharm to boost your productivity when working with data.

This year, we are trying out a new approach with our releases, moving away from a quarterly schedule to more regular monthly feature-rich releases. This change is intended to deliver new features more rapidly and streamline the feedback process. Upgrade to PyCharm 2023.3.4 New AI Assistant…

New actions available in AI Assistant, improved Django Structure tool window and important bug fixes.

PyCharm 2023.3.3: Improvements to Jupyter Notebook Support, AI-Generated Unit Tests, and Async Viewer for the Debugger

The third EAP build brings the long-awaited ability to work with remote Jupyter notebooks, enhancements to the new UI, new Astro support, and more. You can download it from our website, get it from the free Toolbox App, or update to it using snaps for Ubuntu. Download PyCharm 2023.1 EAP L…

Sooner or later in your data science journey, you’ll hit a point where you need to get data from a database. However, making the leap from reading a locally-stored CSV file into pandas to connecting to and querying databases can be a daunting task. In the first of a series of blog posts, we’ll explo…

Making mistakes in your code is a pain, and debugging in Jupyter notebooks can get messy. While Jupyter helpfully displays the full Python traceback, which highlights the lines that have failed, working out exactly what caused the issue in your code can be tricky. I usually end up pulling my code ap…