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Cosmetic fixes

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Nicolas P. Rougier 2016-07-15 08:06:49 -05:00
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100 Numpy exercises.rst
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100 numpy exercises
=====================================
===================
A joint effort of the numpy community
-------------------------------------
This is a collection of exercises that have been collected in the numpy mailing
list, on stack overflow and in the numpy documentation. I've also created some
to reach the 100 limit. The goal of this collection is to offer a quick
reference for both old and new users but also to provide a set of exercices for
those who teach.
The goal is both to offer a quick reference for new and old users and to
provide also a set of exercices for those who teach. If you remember having
asked or answered a (short) problem, you can send a pull request. The format
is:
::
#. Find indices of non-zero elements from [1,2,0,0,4,0]
.. code:: python
# Author: Somebody
print(np.nonzero([1,2,0,0,4,0]))
Here is what the page looks like so far:
http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html
Repository is at: https://github.com/rougier/numpy-100
Thanks to Michiaki Ariga, there is now a
`Julia version <https://github.com/chezou/julia-100-exercises>`_.
If you find an error or think you've a better way to solve some of them, feel
free to open an issue at https://github.com/rougier/numpy-100
#. Import the numpy package under the name ``np`` (★☆☆)

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README.md
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## 100 numpy exercises
[![Binder](http://mybinder.org/badge.svg)](http://mybinder.org:/repo/rougier/numpy-100)
This is a collection of exercises that have been collected in the numpy mailing
list, on stack overflow and in the numpy documentation. I've also created some
to reach the 100 limit. The goal of this collection is to offer a quick
reference for both old and new users but also to provide a set of exercices for
those who teach.
[![Binder](http://mybinder.org/badge.svg)](http://mybinder.org:/repo/rougier/numpy-100)
→ [Test them on Binder](http://mybinder.org:/repo/rougier/numpy-100)
→ [Read them on GitHub](100 Numpy exercises.rst)
[Link to exercices](100 Numpy exercises.rst)