Python Scientific Computing

---
name: python-scientific-computing
version: 1.0.0
description: Python for engineering analysis, numerical computing, and scientific
  workflows using NumPy, SciPy, SymPy
type: reference
author: workspace-hub
category: data
tags:
- python
- numpy
- scipy
- sympy
- numerical-computing
- engineering
- scientific-computing
platforms:
- python
capabilities: []
requires: []
---

# Python Scientific Computing

## When to Use This Skill

Use Python scientific computing when you need:
- **Numerical analysis** - Solving equations, optimization, integration
- **Engineering calculations** - Stress, strain, dynamics, thermodynamics
- **Matrix operations** - Linear algebra, eigenvalue problems
- **Symbolic mathematics** - Analytical solutions, equation manipulation
- **Data analysis** - Statistical analysis, curve fitting
- **Simulations** - Physical systems, finite element preprocessing

**Avoid when:**
- Real-time performance critical (use C++/Fortran)
- Simple calculations (use calculator or Excel)
- No numerical computation needed

## Resources

- **NumPy Documentation**: https://numpy.org/doc/
- **SciPy Documentation**: https://docs.scipy.org/doc/scipy/
- **SymPy Documentation**: https://docs.sympy.org/
- **NumPy for MATLAB Users**: https://numpy.org/doc/stable/user/numpy-for-matlab-users.html
- **SciPy Lecture Notes**: https://scipy-lectures.org/

## Sub-Skills

- [1. NumPy - Numerical Arrays and Linear Algebra (+2)](1-numpy-numerical-arrays-and-linear-algebra/SKILL.md)
- [1. Use Vectorization (+4)](1-use-vectorization/SKILL.md)

## Sub-Skills

- [Example 1: Marine Engineering - Catenary Mooring Line (+5)](example-1-marine-engineering-catenary-mooring-line/SKILL.md)
- [Pattern 1: Load and Process Engineering Data (+2)](pattern-1-load-and-process-engineering-data/SKILL.md)
- [Installation](installation/SKILL.md)
- [CSV Data Processing (+1)](csv-data-processing/SKILL.md)
- [Performance Tips](performance-tips/SKILL.md)