Explorations with column keys for DataFrames

DFVector.jl

importall Base
using DataFrames
type IX 
    df::AbstractDataFrame
end
IX(args...) = IX(DataFrame([args...]'))
length(x::IX) = 1
type DFVector <: AbstractArray{AbstractDataFrame,1}
    df::AbstractDataFrame
end
start(itr::DFVector) = 1
done(itr::DFVector, i::Int) = i > nrow(itr.df)
next(itr::DFVector, i::Int) = (itr.df[i, :], i + 1)
size(itr::DFVector) = (nrow(itr.df), )
length(itr::DFVector) = nrow(itr.df)
getindex(itr::DFVector, i::Union(AbstractVector{Integer}, AbstractVector{Bool}, BitArray)) = DFVector(itr.df[i, :])
getindex(itr::DFVector, i::Int) = IX(itr.df[i, :])
map(f::Function, dfri::DFVector) = [f(row) for row in dfri]
DataFrames.upgrade_vector(v::DFVector) = v
show(io::IO, x::IX) =  for i in 1:ncol(x.df) show(io, x.df[1,i]); print(io, " "); end
show(io::IO, x::DFVector) =  for i in 1:length(x) show(io, x[i]); println(io) end
similar(x::DFVector, T, dims) = Array(T, dims)

function isless(x1::IX, x2::IX)
    lt = x1.df .< x2.df
    gt = x1.df .> x2.df
    for i in 1:length(lt)
        if lt[1,i]
            return true
        elseif gt[1,i]
            return false
        end
    end
    return false
end
function (==)(x1::IX, x2::IX)
    for i in 1:min(ncol(x1.df), ncol(x2.df))
        if x1.df[1,i] != x2.df[1,i]
            return false
        end
    end
    return true
end

srand(10)
N = 10
d = DataFrame(
    a = letters[rand(10:11, N)],
    b = LETTERS[rand(6:7, N)],
    c = letters[rand(23:26, N)],
    x = rand(N),
    y = rand(N)
)
d["ix"] = IndexedVector(DFVector(d[:,[1:3]]))

d[d["ix"] .== IX("j"), :]
d[d["ix"] .== IX("j", "G"), :]
d[d["ix"] .== IX("j", "G", "y"), :]

Note, you need a pretty recent Julia and DataFrames for this code to work.