That section will explain how to configure Jupyter Lab, and in particular how to install new kernels for PySpark, R, Scala and Ruby. It is part of the Python induction for Machine Learning (ML) project, but may be referenced by many other projects. As of end of 2018, that part of the documentation is still to open source (I have documented it privately and still need to do some housekeeping before open sourcing it).
The section on Python virtual environments explains how to install Jupyter Lab within a Python virtual environment. An alternative way is to use a Docker images for Python Jupyter Lab notebooks.