[Query.jl] Way to map many variables to a single function

Here is the code in DataFrames:

@chain DataFrame(tbl) begin
    dropmissing([:NT_GER, :NT_FG, :NT_CE])
    groupby([:TP_SEXO, :CO_TURNO_GRADUACAO], skipmissing=true)
    combine(nrow,
            [:NT_GER, :NT_FG, :NT_CE] .=> mean)
end

how do I do it in Query.jl but using a single instruction to @map to mean. I have to keep repeating myself like this:

Tables.datavaluerows(tbl) |>
    @dropna(:NT_GER, :NT_FG, :NT_CE, :TP_SEXO, :CO_TURNO_GRADUACAO) |>
    @groupby({_.TP_SEXO, _.CO_TURNO_GRADUACAO}) |>
    @map({
        sexo = key(_)[1],
        turno = key(_)[2],
        nrows = length(_),
        NT_GER_mean = mean(_.NT_GER),
        NT_FG_mean = mean(_.NT_FG),
        NT_CE_mean = mean(_.NT_CE)
    }) |> 
    DataFrame

Is there something like?:

@map({
        sexo = key(_)[1],
        turno = key(_)[2],
        nrows = length(_),
       {_.NT_GER, _.NT_FG, _.NT_CE} = mean(_)
})