Advanced and Parallel Python

The Scientific Python Software Stack

This is a brief summary of the most commonly used scientific software/libraries.

Python

The Python language itself: a powerful and easy to learn language that integrates with almost everything imaginable.

Reference: https://www.python.org/

Numpy

The (most) fundamental Python package of scientific Python programming. Mainly known for its fast N-dimensional array implementation. It is the basis of most other scientific libraries.

Reference: http://www.numpy.org/

Scipy

Python-based and open source scientific libraries, ranging from integration to signal processing and from statistics to image processing.

Reference: http://www.scipy.org/

IPython Notebook

This web interface to the IPython shell is an interactive computational environment enabling reproducible research.

Reference: http://ipython.org/notebook.html

Matplotlib

Widely used plotting library, mostly used for visualization and data analytics.

Reference: http://matplotlib.org/

Pandas

An open source data manipulation/analysis library. It offers R-like functionalities like DataFrame objects.

Reference: http://pandas.pydata.org/

… and more!