Jupyter Notebook vs PyCharm: Software Comparison

choose the right thing integrated development environment or data science notebook solutions are the key to increasing productivity and streamlining the research or development process for maximum efficiency. Jupyter Notebook and PyCharm are two popular options that offer their own distinct advantages in different areas of data science and software development.

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What is Jupyter Notebook?

Image: Jupyter Notebook

Jupyter is a browser-based, open-source data science notebook tool that supports Python, Julia, and other dynamic programming languages ​​such as R, Scilab, and Octane. Focused on scripting and related documentation, Jupyter is ideal for data scientists who need a way to build fast data visualizations. However, the source code is saved as HTML and can be read by Jupyter instead of Python.

What is Pycharm?

Image: pycharm

PyCharm is a dedicated IDE tool that aims to provide an end-to-end solution for building full-fledged packages and software including classes in Python. graphical user interface, It also excels in complex environments where multiple scripts interact and need to be managed.

PyCharm’s most popular features include a built-in debugger and smart autocomplete, as well as DevOps tools like version control, making it ideal for developers and software engineers.

Jupyter Notebook vs PyCharm: Comparison Chart

Jupyter Notebook and PyCharm have different features that make each of them data science tools Better for specific applications. For example, Jupyter’s features are more suitable for data analysts and research applications, while PyCharm’s features are designed for developers and software engineering.

Work jupyter notebook PyCharm
smart autofill No Yes
inline code execution using block Yes No
Support for single line charts Yes No
intelligent code analysis No Yes
Integration with popular devices Yes Yes
Face value Free $249 per user billed annually

jupyter notebook and pycharm prices

Jupyter Notebooks provides a 100% open-source solution released under the liberal terms of the Revised BSD License. It is free to access and use, making it an excellent option for companies looking to save on software costs.

In comparison, organizations have to pay to use PyCharm. Solutions start at $249.00 per user for the first year of use. Then the price drops to $199.00 per user for the second year and finally $149.00 for the third year and beyond.

Feature Comparison: Jupyter Notebook vs PyCharm

code execution

Jupyter and PyCharm both let you run your code and provide ways to analyze or determine where errors are coming from. That said, Jupyter is more flexible in this regard, as it allows for single-line execution, which saves time finding coding errors and makes the platform ideal for trial-and-error coding or experimentation (Image A,

Image A

Jupyter notebook interface with numbers and text
Jupyter Notebook’s single-line execution lets you test functions as code, with support for over 40 programming languages. Image: Jupyter Notebook

With PyCharm, all you have to do is complete or modify the entire code snippet in order to run it and inspect the output. As a result, testing or experimenting with code is slow and finding coding errors is a much more laborious task than in Jupyter.

coding features

PyCharm’s autocomplete feature really facilitates rapid development and workflow, and this is something that Jupyter does not provide (picture b, This clever editing feature is the reason why PyCharm is the obvious choice for developers and software engineers, especially those who work exclusively in Python.

picture b

PyCharm code editor interface in dark mode
PyCharm’s intuitive coding interface with intelligent code completion. Image: pycharm

Jupyter also has unique coding features, but these are primarily focused on visualization. This includes the ability to graph or visualize individual lines of code or data, something that PyCharm does not provide. It is a useful tool for data science or research applications where the intended audience of the output is non-technical.


Both tools provide a number of built-in integrations for the framework and other developer productivity tools. Although they share some of the same integrations, there are some tools that are not shared.

Some major integrations for Jupyter that PyCharm does not offer are GitHub, Dropbox, Scala, and TensorFlow. PyCharm provides integration with Django, Kite, Wakatime and Pytest.

Advantages and Disadvantages of Jupyter Notebook


  • Users can access the Markdown language for extensive documentation.
  • Jupyter provides a contemporary, user-friendly, and attractive interface.
  • Users can easily work with different programming languages ​​such as Python, R and Julia.
  • Jupyter provides seamless sharing of images, code, and text in a unified, interactive environment.


  • Notebook JSON file storage can complicate using version control tools like Git for change tracking and collaboration.
  • Reviewers have reported occasional slowness or crashes when dealing with large datasets or performing complex calculations in the software.

Pros and Cons of PyCharm


  • Quick and easy installation process.
  • The solution is user friendly and intuitive.
  • PyCharm provides a large number of efficient shortcuts.
  • Users can avail community support.


  • The premium version of the software can be expensive.
  • The solution requires significant resources, ie requires significant memory and storage space.

review method

It is a technical review using compiled literature researched from relevant databases. The information in this article was gathered from vendor websites or based on collection of user feedback to ensure high quality reviews.

Should your organization use Jupyter Notebook or PyCharm?

When considering an integrated development environment, the decision is often based on personal preference and the platform’s respective applications.

Jupyter is like a data science notebook and its tools and features are tailored for research or data science projects that require data sharing and visualization. The ability to create inline charts and add text, HTML, and other functions in addition to code works towards this goal.

PyCharm is aimed at developers who want to create complex software with GUIs and other features. Smart editing, intelligent analysis and autocompletion all focus on streamlined developer efficiency. PyCharm also has much-needed features for developers, such as version control, safe refactoring, and other tools.

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