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-title = "Jupyter Notebooks"
-description = "How to access and use a Jupyter Notebook"
-weight = 20
-hidden = "true"
-+++
-
-- [Connecting to JupyterHub](#connecting-to-jupyterhub)
-- [Running Code](#running-code)
-- [Opening a Terminal](#opening-a-terminal)
-- [Using Custom Packages](#using-custom-packages)
-
-## Connecting to JupyterHub
------------------------
- 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, go to the address of the cluster, below [Crane](crane.unl.edu) will be used as an example, sign in 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 "Noteboook via SLURM Job | Small (1 core, 4GB RAM, 8 hours)" for light tasks such as debugging or small-scale testing.
-Select the other options based on your computing needs. Note that a SLURM Job will 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]({{< relref "/applications/user_software/using_anaconda_package_manager#using-an-anaconda-environment-in-a-jupyter-notebook-on-crane" >}}).
-
----
-
-