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Examples
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BudiBadu
Online NumPy Compiler
NumPy (Numerical Python) is the fundamental package for scientific computing in Python and serves as the foundation for the entire Python data science ecosystem. Our dedicated online NumPy compiler provides a complete browser environment for working with large, multi-dimensional arrays and matrices, along with a comprehensive collection of mathematical functions to operate on these arrays. NumPy's powerful ndarray object is the cornerstone of modern data analysis, machine learning, and scientific computing in Python.
This compiler includes NumPy 1.14+ with full support for ndarray operations, linear algebra, Fourier transforms, and random number generation, all powered by Pyodide WebAssembly technology. The compiler supports all core NumPy features including array creation, manipulation with powerful indexing and slicing, broadcasting for efficient element-wise operations, and a comprehensive library of mathematical functions covering trigonometric, exponential, and logarithmic operations. Whether you're performing matrix operations, statistical analysis, or scientific computations, our NumPy playground offers instant execution without any setup. You can also upload and use files or folders directly in your code for data processing and numerical workflows. This compiler is online and completely free to use.
Our platform comes with carefully crafted examples covering essential NumPy topics such as array basics, array creation using zeros, ones, identity matrices, random arrays, arange, and linspace functions. You'll learn matrix operations including multiplication, transpose, determinant, and inverse operations, as well as statistical analysis techniques for computing mean, median, standard deviation, percentiles, and correlation coefficients. The examples also demonstrate NumPy's broadcasting rules for efficient computations and linear algebra operations like solving linear equations, eigenvalue problems, and SVD decomposition.
Ideal Use Cases
- Scientific computing and numerical analysis for research and education
- Data preprocessing for machine learning pipelines and model training
- Statistical analysis and modeling with advanced mathematical operations
- Signal and image processing applications in various domains
- Physics and engineering simulations requiring efficient array computations
- Financial calculations and quantitative analysis for trading algorithms
Part of the BudiBadu Ecosystem
Specialized Online Python compiler powered by Pyodide WebAssembly. Run Python Library directly in your browser with zero setup.
Pyodide
WebAssembly
Monaco Editor
Python 3.13