Jupyter defines it's notebooks ("Jupyter Notebooks") as
an open-source web application that allows you to create and share documents that contain live code,
equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation,
statistical modeling, data visualization, machine learning, and much more.
1. To open a Jupyter notebook, [Sign in](https://crane.unl.edu) to crane.unl.edu using your hcc credentials (NOT your
UNL credentials).
{{<figuresrc="/images/jupyterLogin.png">}}
2. Select your prefferred authentication method.
{{<figuresrc="/images/jupyterPush.png">}}
## Running Code
1. Select the "New" dropdown menu and select the file type you want to create.
{{<figuresrc="/images/jupyterNew.png">}}
2. A new tab will open, where you can enter your code. Run your code by selecting the "play" icon.
{{<figuresrc="/images/jupyterCode.png">}}
## Opening a Terminal
1. From your user home page, select "terminal" from the "New" drop-down menu.
{{<figuresrc="/images/jupyterTerminal.png">}}
2. A terminal opens in a new tab. You can enter [Linux commands] ({{<relref"basic_linux_commands">}})
at the prompt.
{{<figuresrc="/images/jupyterTerminal2.png">}}
## Using Custom Packages
Many popular `python` and `R` packages are already installed and available within Jupyter Notebooks.
However, it is possible to install custom packages to be used in notebooks by creating a custom Anaconda
Environment. Detailed information on how to create such an environment can be found at
[Using an Anaconda Environment in a Jupyter Notebook on Crane]({{<relref"using_anaconda_package_manager/#using-an-anaconda-environment-in-a-jupyter-notebook-on-crane">}}).