This repository is an introduction to Jupyter notebooks, a widely used interactive computing environment that is easy enough for 15 year old school children and powerful enough for professional scientists.

Although Jupyter notebooks can used with several programming languages, all examples in this repository are in Python. I will therefore assume you are familiar with the basics of Python.

Jupyter notebooks have the extension .ipynb because they used to be called IPython notebooks. The name 'Jupyter' comes from the three programming languages it is most widely used with: Julia, Python and R.

Make sure you are reading this text on the home page of the repository. Otherwise certain sentences won't make sense.

A Jupyter notebook is a rich, interactive, computing environment. It can include a mix of explanatory text, live code, and the code's output. To work with or on a notebook, a Jupyter environment is required. However, a notebook can also be rendered as a static web page or as a PDF document, for those who just want to read the notebook.

In the file list above this text, click on turbeculosis.ipynb to see how a notebook looks like when rendered as a static web page. You don't need to read the notebook in detail, just skim it. It shows that the output of code can be not just text, but also tables and charts, all in one single integrated document.

Now that you've seen a concrete example of a notebook, read What is the Jupyter Notebook?, a brief introduction by the Jupyter team to the main terminology and features of notebooks.

The notebooks in this repository are as follows.

The audio folder has notebooks that generate, manipulate and play music. Click on the folder name in the list above to see their description.

The images folder has notebooks that load, manipulate and display images. Click on the folder name in the list above to see their description.

complexity.ipynb shows how to measure the run-time of Python code and thereby empirically obtain the complexity of an algorithm.

interaction.ipynb shows how to quickly create interactive interfaces with sliders, checkboxes and dropdown menus. You won't see them when reading this notebook as a static web page.

tuberculosis.ipynb is a very simple example of reproducible research. It shows how to load data from an Excel spreadsheet, analyse and visualise the data, and write up the conclusions. This notebook uses the pandas library and requires the WHO_POP_TB.xls file, which contains World Health Organisation data about the world's population and deaths due to tuberculosis.

turtle.ipynb shows how to draw turtle graphics from a notebook. It only uses Python's built-in turtle library. The graphics themselves appear in a separate window, as notebooks can only include HTML. This notebook includes a simple example of fractal tree drawing.

As mentioned before, if you click on any notebook name at the top of this page, you will see a static rendering of that notebook. You can't execute the code and you can't change the notebook. To do that, you must download the notebooks and open them in the right environment. To download them to your laptop or desktop (I haven't tried on a tablet):

1. Click on the green 'Clone or download' button in the upper right part of this page.
2. You will see a pop-up window with a button 'Download ZIP'. Click on it. The notebooks and data files will be downloaded as a compressed archive: a file with extension .zip. The archive will be in the folder where your web browser usually puts downloaded files.
3. You will need to double-click on the downloaded file to uncompress it, if your browser hasn't done that automatically for you. You should now have a sub-folder named The-Joy-of-Jupyter-master or similar.

Next you need to choose which environment to use for working with notebooks. You have several choices.

The simplest and quickest way of seeing Jupyter notebooks in action, without installing any software or creating a user account (I know it sounds too good to be true), is to use the Try Jupyter! website. It will create a Jupyter environment just for you, already with some demo folders and files that you are free to explore later on. Because the environment is just for you, you can add, delete and edit files as you please. It won't affect anyone else.

You will lose all changes once you close the Try Jupyter! webpage or leave it unattended for too long. You can however download the notebooks you changed to your machine and upload them again in a future session. Try Jupyter! is meant for quick exploration of Jupyter notebooks in short sessions. It is not meant for regular work on notebooks. There are other, better suited environments for that.

Now that you're aware of the advantages and disadvantages of this environment, go to the Try Jupyter! website. After a little while you will see the Notebook Dashboard, which is similar to the file browser on your machine.

Click on the 'Upload' button in the upper right corner of that site. You will get the usual file picker dialog on your machine. Go to the downloads folder, then to the downloaded sub-folder. Select one of the Joy of Jupyter notebooks and any required auxiliary file. Don't select the turtle graphics notebook: it won't work in Try Jupyter!. Click on the 'OK' or 'Choose' button of the file dialog.

The notebook and auxiliary file you selected will now appear at the start of the list of files, with blue 'Upload' buttons. Click on those buttons to confirm the uploading. (The audio notebook and sound file are relatively large and may take a little while to upload.)

After the upload, the files will be in alphabetical order among the list. I suggest you click once or twice on the 'Last Modified' button so that the most recent files are easier to spot, at the start of the list. You can click the 'Name' button once or twice to list the files in ascending or descending alphabetical order.

With the files uploaded, you can start working on the notebook.

First read the Notebook Basics, written by the Jupyter team. The first part has more details about the dashboard, the second is about working with a notebook.

Next, in the dashboard, click on the name of the notebook you uploaded, to open it. Before you start working, I suggest you click on the Help menu and take the 'User Interface Tour'.

As you work on a notebook, don't forget to regularly save it, by clicking on the button with a floppy disk icon, below the File menu.

Once you're done, select File –> Close and Halt. This will stop the kernel that executes the code cells. Afterwards, use your browser's back button to go back to the dashboard. If you forgot to halt any notebooks, they will be listed in green. Click the checkbox next to them. A new menu appears above the file list, with a 'Shutdown' button. Click it.

As mentioned earlier, if you wish to keep a copy of a notebook you changed, you must download it. When you're back in the dashboard, click the checkbox to the left of the file you wish to download. A new 'Download' button appears above the file list. Click on it.

If you have a couple of spare gigabytes on your hard disk, you should install Anaconda. It's freely available for Linux, Mac and Windows. It includes Python, Jupyter, and over hundred libraries. There are two variants of Anaconda: with Python 2 and with Python 3. Make sure you install the latter. Python 2 is no longer developed. Once you have installed Anaconda, launch the Anaconda Navigator. You will see list of installed applications, one being Jupyter Notebook. Click the 'Launch' button below it.

If you don't want or can't install software, there are other web-based providers, like CoCalc, Microsoft Azure Notebooks, and Anaconda Cloud. All of these require to set up a user account, so that your notebooks can be saved between sessions.