Which is Better: PyCharm vs. Jupyter Notebooks?

Compare PyCharm and Jupyter Notebooks for data science projects. Analyze the advantages and disadvantages of each in terms of debugging, interactivity, ease of use, collaboration.

Data science is a rapidly growing field, and as a data scientist, you need to have the right tools to get the job done. One of the most important decisions you’ll make is choosing the right IDE (Integrated Development Environment) for your work. Two of the most popular options for data science are PyCharm and Jupyter Notebooks. In this blog post, we’ll compare PyCharm vs. Jupyter Notebooks and help you decide which one is better for your needs. You can use both of these for free at Saturn Cloud.


PyCharm is a powerful IDE developed by JetBrains, the same company behind IntelliJ IDEA, WebStorm, and other popular IDEs. It’s a full-featured IDE that supports a wide range of programming languages, including Python, Java, JavaScript, and many others. PyCharm is designed to be a one-stop-shop for all your development needs, with features like code completion, debugging, version control, and more.

One of the biggest advantages of PyCharm is its code completion and debugging features. PyCharm’s code completion is one of the best in the industry, with intelligent suggestions for code snippets, class names, and more. Its debugging tools are also top-notch, with support for breakpoints, watches, and other advanced features.

Another advantage of PyCharm is its integration with other JetBrains tools. If you’re already using IntelliJ IDEA or WebStorm, you’ll find that PyCharm integrates seamlessly with these tools, making it easy to switch between them as needed.

However, PyCharm does have some downsides. One of the biggest is its steep learning curve. PyCharm is a complex IDE with a lot of features, and it can take some time to learn how to use them all effectively. Additionally, PyCharm is a paid IDE, with a price tag of $199 per year for the professional version. While there is a free community edition available, it lacks many of the advanced features that make PyCharm so powerful.

Jupyter Notebooks

Jupyter Notebooks, on the other hand, are a web-based IDE that’s designed specifically for data science. Jupyter Notebooks allow you to create and share documents that contain live code, equations, visualizations, and narrative text. They’re a popular choice for data scientists because they allow for easy collaboration and reproducibility.

One of the biggest advantages of Jupyter Notebooks is their ease of use. Jupyter Notebooks are simple to set up and use, with no installation required. You can access them from any device with an internet connection, making them a great choice for remote work or collaboration.

Another advantage of Jupyter Notebooks is their interactivity. Jupyter Notebooks allow you to run code snippets and see the results immediately, making it easy to experiment and iterate quickly. They also support a wide range of programming languages, including Python, R, and Julia.

However, Jupyter Notebooks do have some downsides. One of the biggest is their lack of debugging tools. While Jupyter Notebooks do support debugging, it’s not as robust as PyCharm’s debugging tools. Additionally, Jupyter Notebooks can be less efficient than PyCharm for large-scale projects, as they require more memory and processing power.

Which One is Better for Data Science?

So, which one is better for data science: PyCharm or Jupyter Notebooks? The answer, as with many things in data science, is “it depends.”

If you’re working on a large-scale project or need robust debugging tools, PyCharm is likely the better choice. Its code completion and debugging features are some of the best in the industry, and its integration with other JetBrains tools can make your workflow more efficient.

On the other hand, if you’re working on smaller projects or need to collaborate with others, Jupyter Notebooks may be the better choice. Its ease of use and interactivity make it a great choice for experimentation and collaboration, and its support for multiple programming languages can be a big advantage.

Ultimately, the choice between PyCharm and Jupyter Notebooks comes down to your specific needs as a data scientist. Both tools have their advantages and disadvantages, and the best one for you will depend on your workflow, project size, and other factors.