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# SciPy - Scientific Computing Tool

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### Transcript

• 1. SciPy Marcelo Cure
• 2. Scientific Computing Tool Open Source tool written in Python Set of 12 packages Focused in mathematics, science and engineering
• 3. Core Packages NumPy SciPylibrary Matplotlib Sympy pandas IPython
• 4. NumPy Powerful N-dimensional array objects Tool for integrating C/C++ and Fortran code Useful for numerical work Good performance working with large arrays
• 5. NumPy import numpy arange(15).reshape(3,5) array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14]]) arange( 0, 2, 0.3) array([ 0. , 0.3, 0.6, 0.9, 1.2, 1.5, 1.8]) linspace( 0, 2, 9) array([ 0. , 0.25, 0.5 , 0.75, 1. , 1.25, 1.5 , 1.75, 2. ])
• 6. Matplotlib Lib for generating 2D and 3D charts Emulates MatLab in a Pythonic way Can be used in combination with NumPy for getting good performance with large arrays
• 7. Matplotlib import matplotlib.pyplot as mpl labels= ['Agua', 'terra'] sizes= [75, 25] colors= ['blue', 'brown'] explode = (0, 0.1) mpl.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True) mpl.axis('equal') mpl.savefig('/home/marcelocure/lalala.png') mpl.show()
• 8. Thank you! http://www.scipy.org http://matplotlib.org/ http://www.numpy.org/