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. If the environment is a standard default environment and you select this environment for more than one notebook, multiple notebook kernels are started in the same runtime. If the environment is a Spark environment, the kernel is started in a dedicated Spark runtime.
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 add your own libraries to your environment:
- Load and access data. See Load and access data. Alternatively, to access project assets programmatically, see:
- 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 short video to see how to create a Jupyter notebook and custom environment.
Watch this video to see how to run basic SQL queries on Db2 Warehouse on Cloud data in a Scala notebook.
Watch these videos to see some examples of Scala Notebooks.