Copyright © 2015 Brandon Rhodes and available under the MIT license:

Permission is hereby granted, free of charge, to any person obtaining a

copy of this software and associated documentation files (the

"Software"), to deal in the Software without restriction, including

without limitation the rights to use, copy, modify, merge, publish,

distribute, sublicense, and/or sell copies of the Software, and to

permit persons to whom the Software is furnished to do so, subject to

the following conditions:

The above copyright notice and this permission notice shall be included

in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS

OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF

MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND

NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE

LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION

OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION

WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

The first instance of this tutorial was delivered at PyCon 2015 in

Montréal, but I hope that many other people will be able to benefit from

it over the next few years — both on occasions on which I myself get to

deliver it, and also when other instructors are able to do so.

To make it useful to as many people as possible, I hereby release it

under the MIT license (see the accompanying `LICENSE.txt` file) and I

have tried to make sure that this repository contains all of the scripts

needed to download and set up the data set that we used. I will be

adding detailed setup instructions to this `README.md` file within the

next few days.

Remember that `git` it is not necessary to benefit from materials that

you find on GitHub — simply click the “Download ZIP” button over on the

right-hand side of the project’s front page, and all of the contents

will be delivered to you as a ZIP file instead:

For those who want to follow along with the tutorial at home, here is

the YouTube recording of the 3-hour tutorial at PyCon itself:

I hope that the recording and the exercises in this repository prove

useful if you are interested in learning more about Python and its data

analysis capabilities!

— [Brandon Rhodes](http://rhodesmill.org/brandon/)