A JavaScript library for scientific and statistical computing, offering R-like statistical methods and linear algebra.
Science.js is a JavaScript library for scientific and statistical computing, providing implementations of statistical methods similar to R and linear algebra operations. It enables developers to perform data analysis, statistical testing, and mathematical computations directly in JavaScript environments.
JavaScript developers, data scientists, and researchers who need to perform statistical analysis or linear algebra calculations in web applications or Node.js projects.
It offers a native JavaScript solution for scientific computing, eliminating the need to switch to other languages like R or Python for statistical and linear algebra tasks, with a modular design inspired by D3.js.
Scientific and statistical computing in JavaScript.
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Provides statistical functions similar to R, enabling data analysis and hypothesis testing directly in JavaScript, as mentioned in the README's comparison to R.
Organized into separate modules like science.stats and science.lin, allowing focused functionality and easier integration, based on the README's structure.
Built entirely in JavaScript, making it seamless for use in both browser and Node.js environments without external dependencies, as highlighted in the description.
Project structure is based on D3.js, facilitating integration with data visualization projects, as noted in the README's thanks section.
Only includes two modules (stats and linear algebra), lacking comprehensive scientific computing tools compared to mature libraries in other languages.
The README is brief and primarily covers installation for development, offering little guidance on usage or API details for end-users.
Requires Node.js and NPM installation, plus a make command for dependencies, which adds overhead compared to simpler drop-in libraries.
science.js is an open-source alternative to the following products: