Interactive Python notebook walkthrough

Data science is very much a practical, experience-based activity. Throughout this course, we want to give you the opportunity to experiment with data, using the popular Python programming language.

We have developed an online interactive notebook facility, to allow you to write Python code in your web browser and run it on our servers at the University of Glasgow. This video works through how you might use an interactive notebook. The actual notebook shown in the video is available in the next step, so you can have a go for yourself.

Each fragment of Python code works, but you should feel free to change the code and see what happens. Don’t worry if you make mistakes or break it – that’s normal for coding! If you want to restore the notebook back to its initial state, click the ‘reset’ button in the toolbar at the top.

You can move between panes in the notebook with Shift + Cursor up or Shift + Cursor down. Alternatively you can click on a pane to highlight it. You can run the code in a Python pane with Shift + Enter. Alternatively you click the ‘run’ button in the toolbar at the top.

There are other interactive notebooks throughout the rest of the course, so please ensure you understand how to work with them at this stage.

For advanced users: Although we support browser-based execution of simple notebooks on our server, more adventurous learners may want to download and install local software on your own machines – so you can do data science at home. We recommend the Jupyter Notebook system. This is quite complex to install and configure, but it is the industry standard for basic data science. All of the notebooks we will use in this online course are available for download, and will work with Jupyter Notebook.

If you get stuck with any of these activities, please let us know in the comments section and we will do our best to advise you.