Coding and running a notebook

After you create a notebook, you’re ready to start writing and running code to analyze data.

A notebook runs in a Jupyter kernel in the environment that you specified at the time you created the notebook. Before you start coding, become familiar with the notebook interface and how to code in Markdown to annotate your code.

When you open a new notebook in edit mode, the notebook is considered to be untrusted by the Jupyter service by default. When you run an untrusted notebook, content deemed untrusted will not be executed. Untrusted content includes any Javascript, or HTML or Javascript in Markdown cells or in any output cells that you did not generated.

To tell the service to trust your notebook content and execute all cells:

  1. Click Not Trusted in the upper right corner of the notebook.
  2. Click Trust to execute all cells.

To develop analytic applications in a notebook, follow these general steps:

  1. Import preinstalled libraries or install your own libraries:
  2. Load and access data. See Load and access data. Alternatively, to access project assets programmatically, see Use Python libraries to interact with projects assets.
  3. Prepare and analyze the data with the appropriate methods:
  4. Collaborate with other project members. You can add comments to notebooks by clicking the comment icon (comment icon).
  5. If necessary, schedule the notebook to run at a regular time. See Schedule a notebook.
  6. When you’re not actively working on the notebook, click File > Stop Kernel to stop the notebook kernel and free up resources.

Watch this video to see how to run basic SQL queries in a Scala notebook.

Figure 1. Video iconRun SQL queries in a Scala notebook
This video shows how to run SQL queries in a Scala notebooks.

Watch these videos to see some examples of Scala Notebooks.

Learn more