This repository aims at introducing the basics of Python and of a few useful packages for scientific computing.
The tutorials are given in the form of Jupyter notebooks and supports Python 2 and Python 3. To use Jupyter notebooks, install the Anaconda distribution (https://www.anaconda.com/distribution/#download-section) and refer to the first notebook (Python_X/Introduction_Jupyter_Notebooks.ipynb).
The content of the other notebooks is quickly described below:
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Tutorial_Python.ipynb -> an introduction to Python built-in types (mainly numbers, booleans, lists and dictionaries), commands and syntax (how to use functions, conditionnal statements, loops...).
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Numpy.ipynb -> an introduction to Numpy, a Python package for multi-dimensionnal array manipulation.
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Matplotlib.ipynb -> an introduction to Matplotlib, a plotting library providing a Matlab-like interface for data visualization.
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Scipy.ipynb -> an illustration of the Scipy library on curve-fitting tasks.