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mention the Python Scientific Lecture Notes

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Valentin Haenel
2013-02-21 22:26:12 +01:00
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@@ -10,9 +10,12 @@ is widely used in academia and scientific projects because it is easy to write,
and it performs really well.
Due to its high performance nature, scientific computing in python often refers
to external libraries, typically written in faster languages (like C, or FORTRAN
for matrix operations). The main libraries used are `NumPy`_,
`SciPy`_ and `Matplotlib`_.
to external libraries, typically written in faster languages (like C, or
FORTRAN for matrix operations). The main libraries used are `NumPy`_, `SciPy`_
and `Matplotlib`_. Going into detail about these libraries is beyond the scope
of the Python guide. However, a comprehensive introduction to the scientific
Python ecosystem can be found in the `Python Scientific Lecture Notes
<http://scipy-lectures.github.com/>`_
Libraries
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