Allow multicolumn transformations for AbstractDataFrame

NEWS.md

@@ -2,6 +2,10 @@
 
 ## Breaking changes
 
+* the rules for transformations passed to `select`/`select!`, `transform`/`transform!`,
+  and `combine` have been made more flexible; in particular now it is allowed to
+  return multiple columns from a transformation function
+  [#2461](https://github.com/JuliaData/DataFrames.jl/pull/2461)
 * CategoricalArrays.jl is no longer reexported: call `using CategoricalArrays`
   to use it [#2404]((https://github.com/JuliaData/DataFrames.jl/pull/2404)).
   In the same vein, the `categorical` and `categorical!` functions

docs/src/lib/types.md

@@ -55,7 +55,8 @@ The `ByRow` type is a special type used for selection operations to signal that
 to each element (row) of the selection.
 
 The `AsTable` type is a special type used for selection operations to signal that the columns selected by a wrapped
-selector should be passed as a `NamedTuple` to the function.
+selector should be passed as a `NamedTuple` to the function or to signal that it is requested
+to expand the return value of a transformation into multiple columns.
 
 ## [The design of handling of columns of a `DataFrame`](@id man-columnhandling)
 

docs/src/man/getting_started.md

@@ -627,6 +627,14 @@ julia> select(df, :x2, :x2 => ByRow(sqrt)) # transform columns by row
 ├─────┼───────┼─────────┤
 │ 1   │ 3     │ 1.73205 │
 │ 2   │ 4     │ 2.0     │
+
+julia> select(df, AsTable(:) => ByRow(extrema) => [:lo, :hi]) # return multiple columns
+2×2 DataFrame
+│ Row │ lo    │ hi    │
+│     │ Int64 │ Int64 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 5     │
+│ 2   │ 2     │ 6     │
 ```
 
 It is important to note that `select` always returns a data frame,