Wrap pd.merge with nested columns support

Feature request

It would be great if we allowed joining dataframes on sub-columns, something like that:

import nested_pandas as npd

merged1 = npd.merge(ndf1, df1, left_on="nested.id", right_on="id")
merged2 = npd.merge(ndf1, ndf2, left_on="nested.id", right_on="lc.oid")

Before submitting
Please check the following:

• I have described the purpose of the suggested change, specifying what I need the enhancement to accomplish, i.e. what problem it solves.
• I have included any relevant links, screenshots, environment information, and data relevant to implementing the requested feature, as well as pseudocode for how I want to access the new functionality.
• If I have ideas for how the new feature could be implemented, I have provided explanations and/or pseudocode and/or task lists for the steps.

The issue gives example calls to npd.merge using nested paths such as "nested.id" and "lc.oid". Start by locating the existing merge entry point and related tests, then trace how join keys are resolved. Done means the two demonstrated nested-column joins work and are covered by tests.