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Numerical computations in Python with capabilities to match those of Matlab, Scilab, GNU Octave

Python combined with NumPy, SciPy, Matplotlib and a suitable IDE can rival the capabilities of Matlab, Scilab and GNU Octave. Being a regular programming language and not merely specialized for numerical computations, it is much better at delivering end-user GUI applications.

Tags

  • gnu octave
  • matlab
  • numerical computations
  • numpy
  • python
  • scilab
  • scipy
View Full Description
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    Study Group
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  • Chat
    #p2pu-751-scientific
  • Updates
    36
  • Organizers
    1
  • Participants
    10
  • Followers
    13
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People


Satish Annigeri (organizer) Wouter van den Bos (participant) Leandro Queiroz (participant) mirorakonto (participant) Rhys (participant) florxx (participant) gundamlh (participant) manoliz (participant) zkubratekin (participant) MarciTorres (participant) DS (participant) Jessy Kate Schingler (follower) AJC (follower) Prasanth (follower) Michael White (follower) Hazem Baqaen (follower) Dave Summers (follower) Juanma Dodero (follower) elizabeth7888 (follower) KOE (follower) scls19fr (follower) Simclass (follower) Guille (follower) Amy Busch (follower)

Tasks


  • Setting Up a Scientific Python Environment
  • Using IPython and IPython Notebook
  • Creating NumPy Arrays and Exploring Their Attributes
  • Quick Ways to Create Arrays
  • Reshaping Arrays
  • Array Slicing
  • Plotting Graphs with Matplotlib

External Links


  • Python
  • NumPy
  • SciPy
  • Matplotlib
  • Scientific Python Lecture Notes
    DS
    DS at Getting Started with Scientific Python
    started following Getting Started with Scientific Python study group.
    03 Dec 2015 via courses.p2pu.org

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