This tutorial is created for use in Python introductory courses at Hanze University of Applied Science, Groningen, The Netherlands. You are free to use it for yourself; however see the LICENCE.TXT note. The notebooks are bundled into an ebook that can be found here: https://michielnoback.github.io/pybook.
This repo contains a series of notebooks introducing programming concepts in Python in a data science
setting.
You can view these notebooks here on github (simply click any file with the ipynb extension),
on NB viewer (nice & fast, but static) or
on Binder (interactive, but much slower).
Here are direct links to both:
If you don't trust links: In NBviewer, simply paste the URL of this repository in the text field and select one of the notebooks, or paste the URL of a single notebook file directly. In Binder it works the same. Enter the URL of this repo and press "launch".
If you wish to work on the exercises, the hints will not look very nice or won't work at all in NBviewer and some IDEs. MyBinder seems OK though.
For optimal experience with the exercises and interactive studying of the material, I suggest you either
- clone the repo to your local machine, or
- download the repo as zip file (click on green button "Code" near the top of the page) unpack on a suitable location
- in github.com, go to the notebook you wish to work on, open it, click "raw", right-mouse-click on the contents and select "save as". Be sure to remove the
.txtextension that may be added.
And open with Jupyter Notebook.
A concise Python3 cheat sheet.
A Python3 extensive cheat sheet.
A Jupyter Notebook cheat.
Copyright (C) 2022-2023 Michiel Noback, Hanze University of Applied Science, Groningen, The Netherlands
See LICENCE.TXT