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NumPy

data-science

Fundamental library for numerical computing in Python

25M/week → Stable

Features

arraysnumericalscientificmath

Pros and Cons

Ventajas

  • + Very fast vectorized operations
  • + Foundation of Python scientific ecosystem
  • + Efficient multidimensional arrays
  • + Wide collection of mathematical functions
  • + Excellent documentation

Desventajas

  • - Only for numerical data
  • - No native GPU support
  • - Syntax can be confusing at first

Use Cases

  • Linear algebra and matrices
  • Image processing
  • Scientific computing
  • Base for pandas and scikit-learn
  • Numerical simulations

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