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.
To tell the service to trust your notebook content and execute all cells:
- Click Not Trusted in the upper right corner of the notebook.
- Click Trust to execute all cells.
To develop analytic applications in a notebook, follow these general steps:
- Import preinstalled libraries or install your own libraries:
- Load and access data. See Load and access data. Alternatively, to access project assets programmatically, see Use Python libraries to interact with projects assets.
- Prepare and analyze the data with the appropriate methods:
- Collaborate with other project members. You can add comments to notebooks by clicking the comment icon ().
- If necessary, schedule the notebook to run at a regular time. See Schedule a notebook.
- 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.
Watch these videos to see some examples of Scala Notebooks.