ndarrays offers numerical arrays which is a comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more like NumPy, Scipy, Scikit-learn, Statistics, Six Sigma Functions, D3 Graphs for scientific graphs. The goal was to be as near as NumPy as possible, however, a combination of a few packages were being done to make this a comprehensive port for major Python Scientific packages.

The version 0.0.2 will start having the actual usable ndarrays which is a python numpy like module.

• rlib:

• regression:

• pickle:

• extenders:

• stats:

• streamStats:

• pyc: Usage:

const { loadPyodide } = require("ndarrays").pyc;

async function main() {
  let pyodide = await loadPyodide();
  console.log(pyodide.runPython(`
    import sys
    sys.version
  `));
};
main();

Following Packages have been used. A comprehensive package documentation will be done for the package.

• atoll: ^0.7.4,
• blasjs: ^1.0.15,
  • Basic Linear Algebra SubPrograms (BLAS)
• d3-regression: ^1.3.10,
  • Linear, Exponential, Logarithmic, Quadratic, Polynomial, Power law, LOESS
• datalib: ^1.9.3,
• extenders: ^0.0.2,
• jerzy: ^0.2.1,
• lib-r-math.js: ^2.0.0,
• mathjs: ^11.8.2,
• mod-pickle: ^0.0.3,
• natural: ^6.5.0,
• pyodide: ^0.23.3,
• scientist.js: ^0.0.1,
  • Liner Algebra, Statistics
• simple-statistics: ^7.8.3,
• stream-statistics: ^0.4.0,
• vega-statistics: ^1.9.0