Users report that PyCharm excels in its "File Management" capabilities, with a score of 8.9, allowing for efficient organization of projects and files, while The Jupyter Notebook received a lower score of 8.3, indicating some limitations in managing larger projects.
Reviewers mention that PyCharm's "Customization" options are robust, scoring 8.7, which allows developers to tailor their environment extensively, whereas The Jupyter Notebook, with a score of 7.8, offers fewer customization features, making it less flexible for personalized workflows.
G2 users highlight that PyCharm's "Straight-Out-the-Box Functionality" is impressive, scoring 8.8, as it provides a comprehensive set of tools for development right after installation, while The Jupyter Notebook, scoring 8.4, may require additional setup for certain functionalities.
Users on G2 report that PyCharm's "Help Guides" are particularly helpful, with a score of 8.6, providing extensive documentation and resources, while The Jupyter Notebook's guides, scoring 8.2, are seen as less comprehensive, which can hinder new users.
Reviewers say that PyCharm's "Patching & Updates" process is efficient, scoring 8.8, ensuring users have access to the latest features and fixes promptly, while The Jupyter Notebook, with a score of 8.3, may not always deliver updates as swiftly, leading to potential delays in accessing new functionalities.
Users report that both products have high "Ease of Use" ratings, with PyCharm at 9.1 and The Jupyter Notebook at 8.9, but many users mention that PyCharm's interface is more intuitive for complex projects, while The Jupyter Notebook shines in simplicity for data analysis tasks.
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PyCharm
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Do you have any plans to keep allowing users to save jupyter notebooks without obligating them to use "cloud services"?
1 Comment
TM
I always encourage students to have a local copy. I just wish there was an easier way to run it locally on Win10/Mac. Anaconda makes it simpler but it is...Read more
What are the features of Jupyter notebook?
1 Comment
DG
1.Code cells for writing and editing code.
2.Markdown cell for writing comments and/or code functions.
3.Raw Jupyter NBConvert cells.
4.A support for...Read more
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