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SciPy alternatives
3 tools to consider instead of SciPy, shown against it.
| SciPy | statsmodels | R | Julia | |
|---|---|---|---|---|
| Vendor | SciPy developers (NumFOCUS-sponsored open-source project) | statsmodels developers (NumFOCUS-sponsored open-source project) | The R Foundation | Julia open-source project (NumFOCUS-sponsored) |
| Pricing model | Open source + paid options | Open source + paid options | Open source + paid options | Open source + paid options |
| Free tier | Yes | Yes | Yes | Yes |
| Deployment | Self-hosted | Self-hosted | Self-hosted | Self-hosted |
| Open source | Yes (BSD-3-Clause) | Yes (BSD-3-Clause) | Yes (GPL-2.0-or-later) | Yes (MIT) |
| Best for | Python developers who need numerical and statistical primitives underneath higher-level analytics tools. | Python-based analysts and econometricians who need rigorous statistical inference, not just predictive accuracy. | Statisticians, academic researchers, and analytics engineers doing custom statistical modeling and visualization. | Quantitative researchers and engineers needing high-performance statistical simulation without dropping to C. |
| Pricing | Free and open source; no commercial tiers. Pricing has not been verified yet — see the vendor's site. | Free and open source; no commercial tiers. Pricing has not been verified yet — see the vendor's site. | Free and open source; no paid tiers for the language itself. Commercial support and hosted environments are sold separately by third parties (e.g. Posit). Pricing has not been verified yet — see the vendor's site. | Free and open source under the MIT license; JuliaHub sells separate paid cloud and enterprise services built on top of the language. Pricing has not been verified yet — see the vendor's site. |
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