DataSpell vs Spyder
Side-by-side comparison for macOS
DataSpell
8.0IDE for Professional Data Scientists
Spyder
8.0Scientific Python IDE
| Metric | DataSpell | Spyder |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 8.0 |
| 30-day Installs | 18 | 89 |
| 90-day Installs | 60 | 288 |
| 365-day Installs | 361 | 1.7K |
| Version | 2026.1.1,261.23567.176 | 6.1.4 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | — | 9.2K |
| GitHub Forks | — | 1.8K |
| Open Issues | — | 1.3K |
| License | — | MIT |
| Language | — | Python |
| Last GitHub Commit | — | 1mo ago |
| First Seen | Aug 9, 2023 | Nov 4, 2013 |
Reviews
DataSpell
DataSpell is a professional IDE designed specifically for data scientists, offering robust support for Python and R, notebook editing, and integration with tools like Jupyter and Pandas. It is tailored for those who need a seamless environment for data analysis and scientific computing.
An integrated development environment tailored for data science tasks, supporting Python and R.
Pros
- + Strong support for Python and R, essential for data science
- + Integrated notebook editing for Jupyter and similar tools
- + Credibility and features from JetBrains, known for quality IDEs
Cons
- - Still maturing, with some features limited compared to established IDEs
- - Limited ecosystem compared to other JetBrains products
Spyder
Spyder is a powerful scientific Python IDE designed for data analysis and visualization. It integrates seamlessly with tools like matplotlib, IPython, and numpy, making it ideal for researchers and data scientists.
Spyder provides a comprehensive integrated development environment for scientific computing in Python.
Pros
- + Fully featured scientific IDE with robust Python integration
- + Open-source and actively maintained
- + Cross-platform compatibility
Cons
- - Steep learning curve for new users
- - Potential performance issues on older systems