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Introducing Jupyter Notebooks

Navigate to the companion material directory in the terminal.

On Unix machines such as Mac or Linux, command-line navigation can be done using ls to display directory contents and cd to change directories. On Windows machines, use dir to display directory contents and use cd to change directories instead. If, for example, you want to change the drive from C: to D:, you should execute d: to change drives.

Start a new local Notebook server here by typing the following into the terminal: jupyter notebook.
A new window or tab of your default browser will open the Notebook Dashboard to the working directory. Here, you will see a list of folders and files contained therein.
Click on a folder to navigate to that particular path and open a file by clicking on it. Although its main use is editing IPYNB Notebook files, Jupyter functions as a standard text editor as well.
Reopen the terminal window used to launch the app. We can see the NotebookApp being run on a local server. In particular, you should see a line like this:
[I 20:03:01.045 NotebookApp] The Jupyter Notebook is running at: http:// localhost:8888/?token=e915bb06866f19ce462d959a9193a94c7c088e81765f9d8a
Going to that HTTP address will load the app in your browser window, as was done automatically when starting the app. Closing the window does not stop the app; this should be done from the terminal by typing Ctrl + C.

Close the app by typing Ctrl + C in the terminal. You may also have to confirm by entering y. Close the web browser window as well.
When loading the NotebookApp, there are various options available to you. In the terminal, see the list of available options by running the following:
jupyter notebook –-help.

One such option is to specify a specific port. Open a NotebookApp at local port 9000 by running the following:
jupyter notebook --port 9000
The primary way to create a new Jupyter Notebook is from the Jupyter Dashboard. Click New in the upper-right corner and select a kernel from the drop-down menu (that is, select something in the Notebooks section):

Kernels provide programming language support for the Notebook. If you have installed Python with Anaconda, that version should be the default kernel. Conda virtual environments will also be available here.

Virtual environments are a great tool for managing multiple projects on the same machine. Each virtual environment may contain a different version of Python and external libraries. Python has built-in virtual environments; however, the Conda virtual environment integrates better with Jupyter Notebooks and boasts other nice features. The documentation is available at https://conda.io/docs/user-guide/tasks/manage-environments.html.

With the newly created blank Notebook, click on the top cell and type print('hello world'), or any other code snippet that writes to the screen. Execute it by clicking on the cell and pressing Shift + Enter, or by selecting Run Cell in the Cell menu.

Any stdout or stderr output from the code will be displayed beneath as the cell runs. Furthermore, the string representation of the object written in the final line will be displayed as well. This is very handy, especially for displaying tables, but sometimes we don't want the final object to be displayed. In such cases, a semicolon (; ) can be added to the end of the line to suppress the display.

New cells expect and run code input by default; however, they can be changed to render Markdown instead.

Click into an empty cell and change it to accept Markdown-formatted text. This can be done from the drop-down menu icon in the toolbar or by selecting Markdown from the Cell menu. Write some text in here (any text will do), making sure to utilize Markdown formatting symbols such as #.
Focus on the toolbar at the top of the Notebook:

There is a Play icon in the toolbar, which can be used to run cells. As we'll see later, however, it's handier to use the keyboard shortcut Shift + Enter to run cells. Right next to this is a Stop icon, which can be used to stop cells from running. This is useful, for example, if a cell is taking too long to run:

New cells can be manually added from the Insert menu:

Cells can be copied, pasted, and deleted using icons or by selecting options from the Edit menu:

Cells can also be moved up and down this way:

There are useful options under the Cell menu to run a group of cells or the entire Notebook:

Experiment with the toolbar options to move cells up and down, insert new cells, and delete cells.

An important thing to understand about these Notebooks is the shared memory between cells. It's quite simple: every cell existing on the sheet has access to the global set of variables. So, for example, a function defined in one cell could be called from any other, and the same applies to variables. As one would expect, anything within the scope of a function will not be a global variable and can only be accessed from within that specific function.

Open the Kernel menu to see the selections. The Kernel menu is useful for stopping script executions and restarting the Notebook if the kernel dies. Kernels can also be swapped here at any time, but it is unadvisable to use multiple kernels for a single Notebook due to reproducibility concerns.
Open the File menu to see the selections. The File menu contains options for downloading the Notebook in various formats. In particular, it's recommended to save an HTML version of your Notebook, where the content is rendered statically and can be opened and viewed "as you would expect" in web browsers.

The Notebook name will be displayed in the upper-left corner. New Notebooks will automatically be named Untitled.

Change the name of your IPYNB Notebook file by clicking on the current name in the upper-left corner and typing the new name. Then, save the file.
Close the current tab in your web browser (exiting the Notebook) and go to the Jupyter Dashboard tab, which should still be open. (If it's not open, then reload it by copy and pasting the HTTP link from the terminal.)

Since we didn't shut down the Notebook, we just saved and exited, it will have a green book symbol next to its name in the Files section of the Jupyter Dashboard and will be listed as Running on the right side next to the last modified date. Notebooks can be shut down from here.

Quit the Notebook you have been working on by selecting it (checkbox to the left of the name) and clicking the orange Shutdown button:

If you plan to spend a lot of time working with Jupyter Notebooks, it's worthwhile to learn the keyboard shortcuts. This will speed up your workflow considerably. Particularly useful commands to learn are the shortcuts for manually adding new cells and converting cells from code to Markdown formatting. Click on Keyboard Shortcuts from the Help menu to see how.