Reach the feature parity between converting columns and adding columns operations

**The problem:** no feature parity between converting columns and adding columns

We have toDataFrame for converting list to `DataFrame` reflectively. unfold for converting column to `ColumnGroup` reflectively
I think we lack some logical symmetry when it comes to doing same what unfold does, but ADDING a column instead. If we expect that it's sometimes desirable to convert Column->ColumnGroup according to T properties, seems natural that add should allow the same

Possible options:
```
df.add {
"" from properties { }
"" from unfold { }
unfold { } into "abc"
}
```

Start by comparing the existing toDataFrame and unfold operations with the df.add API shown in the issue. Determine which column-to-ColumnGroup conversions should be supported when adding columns and agree on the intended syntax and behavior. Done means the add operation provides the requested reflective parity and its behavior is covered by the project's relevant tests.

Written by the indexing model from the issue text.