Jupyter Notebook and PyCharm are data science notebook and development tools respectively. Compare features to see which is best for you.
Choosing the right thing integrated development environment (IDE), or data science notebook, solution is the key to increasing productivity and streamlining the research or development process for maximum efficiency. Jupyter Notebook and PyCharm are two popular choices that offer their own distinct advantages in different fields of data science and software development.
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What is Jupyter Notebook?
Jupiter 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. Jupyter focuses on scripts and related documentation and is ideal for data scientists who need a way to create fast data visualizations. However, the source code is saved as HTML and can be read by Jupyter instead of Python.
What is PyCharm?
PyCharm is a dedicated IDE tool aimed at providing a complete solution for creating full-fledged packages and software in Python, including classes and graphical user interfaces (GUIs)† It also excels in complex environments where multiple scripts communicate with each other and need to be managed.
PyCharm’s most popular features include a built-in debugger and smart auto-complete, as well as DevOps tools such as version control, making it ideal for developers and software engineers.
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jupyter vs. PyCharm Feature Comparison
Jupyter Notebook and PyCharm have different features, making each tool better for specific applications. For example, Jupyter’s features are more suited to data analysts and research applications, while PyCharm’s features are designed for developers and software engineering.
| Feature | Jupyter notebook | PyCharm |
|---|---|---|
| Smart Autofill | no | Yes |
| Execution of inline code with blocks | Yes | no |
| Support for single-line charts | Yes | no |
| Intelligent code analysis | no | Yes |
| Integration with popular tools | Yes | Yes |
Code execution
Both Jupyter and PyCharm allow you to run your code on the spot and provide ways to analyze or determine where errors are coming from. While Jupyter is more flexible in this regard, as it allows for single-line runs, which saves time finding coding errors and makes the platform ideal for trial-and-error coding or experimentation.
With PyCharm, you would have to complete or modify the entire code snippet to run it and observe the output. As a result, code testing or experimentation is slower and finding coding errors is a much more painstaking task compared to Jupyter.
Coding Features
PyCharm’s auto-complete feature really allows for faster development and workflow, and it’s something Jupyter doesn’t offer. This clever editing feature is why PyCharm is clearly the choice for developers and software engineers, especially those who work exclusively in Python.
Jupyter also has unique coding features, but mainly focuses on visualization. This includes the ability to graph or visualize individual lines of code or data, something PyCharm does not provide. This is a useful tool for data science or research applications where the intended audience of the output is non-technical.
Integrations
Both tools offer many built-in integrations for frameworks and other developer productivity tools. While they share some of the same integrations, there are some tools that are not shared.
Some key integrations for Jupyter that PyCharm doesn’t offer are GitHub, Dropbox, Scala, and TensorFlow. PyCharm offers integration with Django, Kite, Wakatime and Pytest.
Choosing between Jupyter and PyCharm
When considering an integrated development environment, the decision is often based on personal preference and the platforms’ respective applications.
Jupyter is more of 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 add inline charts and add text, HTML, and other functions in addition to the code all work towards this goal.
PyCharm is aimed at developers who want to create complex software complete with GUIs and other features. The smart editing, intelligence analysis, and auto-completion are all aimed at streamlined developer efficiency. PyCharm also has much-needed features for developers, such as version control, secure refactoring, and other tools.
