Explanation of full DataFrame to Dataset translation

Using to_xarray() on a DataFrame doesn't get me to the Dataset I want, because typically I want some of the DataFrame's columns to be coordinates, and some Data Variables.

This Stack Exchange question and answer give part of the solution: https://stackoverflow.com/questions/59672658/reassigning-xarray-data-variable-to-xarray-coordinate

This tells us how to turn some of the data variables in the translated data set into coordinates. But that's not the full solution, because we also need the coordinates to be applied to the data variables. Somehow we need to add the variables that are now coordinates as dimensions.

This is probably somewhere in the docs, but it isn't pulled together into a big picture answer. It would be great if there was an end-to-end example of taking a pandas DataFrame, partitioning variables into coordinates and data variables, and being able to use the resulting coordinates (with Dataset.sel()) to address the data variables.

If that is in the online docs, I don't know how to find it. Thanks!

Start with the existing documentation for pandas DataFrame.to_xarray(), Dataset coordinates, dimensions, and Dataset.sel(), using the linked Stack Exchange question as context. Done means an end-to-end example shows how to partition DataFrame columns into coordinates and data variables, apply those coordinates to the data variables, and select them with Dataset.sel().