Jupyter.md

title = "Jupyter Notebooks on Crane"
description = "How to access and use a Jupyter Notebook"
weight = 20

• [Connecting to Crane] (#connecting-to-crane)
• [Running Code] (#running-code)
• [Opening a Terminal] (#opening-a-terminal)
• [Using Custom Packages] (#using-custom-packages)

Connecting to Crane

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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 to crane.unl.edu using your hcc credentials (NOT your campus credentials). {{< figure src="/images/jupyterLogin.png" >}}

2. Select your preferred authentication method.

   {{< figure src="/images/jupyterPush.png" >}}

3. Choose a job profile. Select "Local Jupyter Notebook" for light tasks such as debugging or small-scale testing. Select the other options based on your computing needs. Note that a local Jupyter Notebook will save to your "home" directory, while the other options save to your "work" directory.

{{< figure src="/images/jupyterjob.png" >}}

Running Code

1. Select the "New" dropdown menu and select the file type you want to create.

{{< figure src="/images/jupyterNew.png" >}} 2. A new tab will open, where you can enter your code. Run your code by selecting the "play" icon.

{{< figure src="/images/jupyterCode.png">}}

Opening a Terminal

1. From your user home page, select "terminal" from the "New" drop-down menu. {{< figure src="/images/jupyterTerminal.png">}}
2. A terminal opens in a new tab. You can enter [Linux commands] ({{< relref "basic_linux_commands" >}}) at the prompt. {{< figure src="/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.

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