SciPy 2016 NumPy tutorial
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SciPy2016 tutorial: Introduction to NumPy

This repository contains all the material needed by students registered for the Numpy tutorial of SciPy 2016 on Monday, July 11th 2016.

For a smooth experience, you will need to make sure that you install or update your Python distribution and download the tutorial material before the day of the tutorial as the Wi-Fi at the AT&T center can be flaky.

Python distribution and Packages needed

If you don't already have a working python distribution, by far the easiest way to get everything you need for this tutorial is to download Enthought Canopy (, the free version is sufficient), or Continuum's Anaconda (

If you have the choice, I recommend to use a Python 2.7 distribution, which is what I will be using and my material as been tested with that. If you have a Python 3.4+ version, you should be fine, though you might have to replace a print statement (print a) by the print function (print(a)) in some of the solution files.

To be able to run the examples, demoes and exercises, you must have the following packages installed:

  • numpy 1.10+
  • matplotlib 1.5+
  • ipython 4.0+ (for running, experimenting and doing exercises)
  • nose (only to test your distribution, see below)

If you use Canopy, everything you need will be installed by default. If you use conda, you can create a new environment using the following command:

$ conda create -n numpy-tutorial python=2 numpy matplotlib nose ipython

To test your installation, please execute the script. The output should look something like this:

$ python
Ran 4 tests in 0.162 s


Content needed

This GitHub repository is all that is needed in terms of tutorial content. The simplest solution is to download the material using this link:

If you're familiar with Git, you can also clone this repository with:

$ git clone

It will create a new folder named SciPy2016_numpy_tutorial/ with all the content you will need: the slides I will go through (slides.pdf), and a folder of exercises.

As you get closer to the day of the tutorial, it is highly recommended to update this repository, as I will be improving it this week. To update it, open a command prompt, move into the SciPy2016_numpy_tutorial/ folder and run:

$ git pull

Questions? Problems?

Questions? Problems? Don't wait, shoot me and the rest of the group an email on the tutorial mailing list:!forum/scipy-2016-numpy-tutorial