Handling VSCode kernel crashes

When doing memory-intensive operations in VSCode - e.g. working with large pandas dataframes - the kernel can crash with the following error:

The kernel crashed while executing code in the current cell or a previous cell. View Jupyter log for further details.

Increasing the memory available (e.g. in GitHub Codespaces) or making the operation less memory intensive (e.g. by reading in and operating on data in chunks) can fend off these errors.

Example

Reading in a dataframe with 5,000,000 records and carrying out an explode() operation was resulting in an error when working in the basic tier of Codespace (2-core with 8GB RAM). Increasing this to an 8-core Codespace with 32GB RAM rectified the problem.