Python Científico

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Uma olhada no python pelos olhos da ciência! Um pouco do porquê python, o que existe por aí e como fazer (apenas live).

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Python Científico

  1. 1. Python Científico
  2. 2. Márcio Valença Ramos
  3. 3. CUBO
  4. 4. Vamos falar de Ciência
  5. 5. Vamos falar de Python
  6. 6. Beautiful & “Fast”
  7. 7. Mas e o ?
  8. 8. $$
  9. 9. Liberdade
  10. 10. ; Em muitas linguagens: Fim de linha Em Python: Inútil No Matlab: Suprima saída para o stdout
  11. 11. () count(2) Count é uma função? Um vetor?
  12. 12. WAT
  13. 13. http://www.pyzo.org/python_vs_matlab.html
  14. 14. + = 2 2 2
  15. 15. SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.
  16. 16. Peças deste Lego
  17. 17. NumPy is the fundamental package for scientific computing with Python. It contains among other things: • A powerful N-dimensional array object • Sophisticated (broadcasting) functions • Tools for integrating C/C++ and Fortran code • Useful linear algebra, Fourier transform, and random number capabilities
  18. 18. The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.
  19. 19. matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python scripts, the python and ipython shell (ala MATLAB or Mathematica), web application servers, and six graphical user interface toolkits.
  20. 20. IPython provides a rich architecture for interactive computing with: • Powerful interactive shells (terminal and Qt-based). • A browser-based notebook with support for code, text, mathematical expressions, inline plots and other rich media. • Support for interactive data visualization and use of GUI toolkits. • Flexible, embeddable interpreters to load into your own projects. • Easy to use, high performance tools for parallel computing.
  21. 21. SymPy is a Python library for symbolic mathematics. It aims to become a full- featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible.
  22. 22. pandas is an open source, BSD-licensed library providing high-performance, easy-to- use data structures and data analysis tools for the Python programming language.
  23. 23. scikit-learn Machine Learning in Python: • Simple and efficient tools for data mining and data analysis • Accessible to everybody, and reusable in various contexts • Built on NumPy, SciPy, and matplotlib • Open source, commercially usable - BSD license
  24. 24. #NumPy
  25. 25. #SymPy
  26. 26. #Scikit-learn
  27. 27. #Juntando várias
  28. 28. Dúvidas?
  29. 29. Obrigado! slideshare.net/marrciovr cubomarrcio@gmail.com facebook.com/marrciovr

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