Transform dataframe columns using column selector (Cols) fails

Question

I am wondering why I cannot use the Cols column selector in transform to change a dataframe column. For instance:

df = DataFrame(x = 1:5, y = 6:10)
transform(df, [:x, :y] .=> v -> v .+ 100)    # OK
df[!, Cols(1:2)] .= df[!, Cols(1:2)] .+ 100  # OK

transform(df, Cols(1:2) .=> v -> v .+ 100)   # MethodError: no method matching length(::Cols{Tuple{UnitRange{Int64}}})

I've read in the DataFrames documentation that says column selectors such as Cols, Between, Not, and All can be used in transform, among others, but yet I get this error.

Thanks for any pointers.

Answer 1

These selectors can be used when they are passed to transform directly. Here you are using broadcasting with .=> (note the dot), so you are not passing them directly to transform, but instead try pass the following:

julia> Cols(1:2) .=> v -> v .+ 100
ERROR: MethodError: no method matching length(::Cols{Tuple{UnitRange{Int64}}})

The error you observe is not emitted by DataFrames.jl but by Julia base.

What you need to do is to use names to make things work:

julia> names(df, Cols(1:2)) .=> v -> v .+ 100
2-element Vector{Pair{String, var"#7#8"}}:
 "x" => var"#7#8"()
 "y" => var"#7#8"()

and in consequence the following works:

 transform(df, names(df, Cols(1:2)) .=> v -> v .+ 100)

In the future the functionality you request might be added but it requires changes in DataAPI.jl, see here.

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EDIT

As signaled in the original answer in DataFrames.jl 1.3 the functionality has been added and now you can do transform(df, Cols(1:2) .=> v -> v .+ 100) without error. See https://bkamins.github.io/julialang/2021/12/17/selectors.html for an explanation how it works now.