Starter Guide to a Jupyter Notebook
The Jupyter Notebook is a very powerful tool for creating and presenting data science projects. It can combine code with visualizations, narrative text, mathematical equations and other media. Data scientists use it to write their code, document it, run it, look at the outcome and visualize data in the same environment!
Installation
The best way to get started with Jupyter Notebooks is by installing Anaconda. Anaconda is the most popular platform for data science and comes with some handy tools (like Jupyter) and libraries. To put it simply, Anaconda installs a bunch of tools and packages for you at once.
- To download Anaconda, go to www.anaconda.com/download and find the download link for your operating system. Make sure you download the Python 3.6 version. There will be two options for the download 64-bit or 32-bit. If you’re unsure of what system type you have, refer to one of these:
For Windows:
https://support.microsoft.com/en-us/help/13443/windows-which-operating-system
For Mac:
2. Click on the downloaded file and run through the install process. (This can take some time)
3. Go to Launchpad (for Mac) or Start Menu (for windows) and look for Anaconda Navigator and open it.
Running Jupyter
From the Anaconda Navigator, select Jupyter Notebook. This is your notebooks dashboard, you can see all your files and folders here. It’s designed to help you manage your notebooks. You might notice that the URL is localhost:8888. It indicates that the content is being served from your local machine: your own computer.
Creating your first notebook
All that is left is opening a new notebook. On the top right you should see an option called New.
Use that to create a new notebook. Make sure you choose Python3 here.
Writing in your first notebook
You should be able to see a cell (textbox) here. Type:
print(“Hello World!”)
here and hit Run from the menu bar.. If you see the following screen, congratulations! You have written your first python program in a jupyter notebook.
Saving and Closing
Jupyter usually saves your changes automatically but make sure you save your work before exiting. Once you’re done, click the Logout button on the top right because you don’t want to let your notebook server running.