Universal table transformer combining univariate transformations dispatched on schema

It has been proposed on Slack that it be possible to have a single table transformer that transforms individual columns according to user-specified univariate transformations. This sounds like a good idea, which would also force some uniformity that's a little bit lacking in the current collection of table transformers.

1. In the most general case I can imagine implementing, the univariate transformer that applies to a particular column is defined by a function that operates on both the name and scitype of the the column (as encoded in the table schema). This has the disadvantage that the user must specify a function with two arguments - or interact through some other complicated interface.

2. The alternative would be a compositional approach. Each tabular transformer only carries out a single univariate transformer, applying to all specified names and scitypes (or "not"-names and "not"-scitypes, through ignore Boolean parameter), which would cover all conceivable use-cases. (columns not referred to are left alone). However, as we are currently locked into Tables.jl (which are non-mutable in general) we get a lot more copying of data.

Thoughts anyone?

Start by reviewing the current collection of table transformers and the Tables.jl schema and mutability constraints described in the issue. Compare the function-based and compositional approaches, then define the user-facing dispatch behavior and confirm that all specified columns are transformed while unspecified columns remain unchanged.