Deserialization as Vector{SubArray} breaks `push!` on DataFrame

I'm using Arrow v2.7.2 with DataFrames v1.6.1 on Julia 1.10, and am running into an issue that seems to stem from Arrow.jl deserializing my `Vector{Vector{T}}` columns as `Vector{SubArray{...}}`:

```julia
julia> using Arrow, DataFrames

julia> df = DataFrame(foo=Vector{Int}[]);

julia> push!(df, [[1,2,3]])
1×1 DataFrame
Row │ foo
│ Array…
─────┼───────────
1 │ [1, 2, 3]

julia> Arrow.write("/tmp/test.arrow", df)
"/tmp/test.arrow"

julia> df2 = copy(DataFrame(Arrow.Table("/tmp/test.arrow")));

julia> typeof(df2.foo)
Vector{SubArray{Int64, 1, Primitive{Int64, Vector{Int64}}, Tuple{UnitRange{Int64}}, true}} (alias for Array{SubArray{Int64, 1, Arrow.Primitive{Int64, Array{Int64, 1}}, Tuple{UnitRange{Int64}}, true}, 1})
```

This breaks certain `push!`es on the dataframe, which I haven't been able to reproduce in isolation, but which looks as follows:

```
MethodError: Cannot `convert` an object of type Vector{Int64} to an object of type SubArray{Int64, 1, Arrow.Primitive{Int64, Vector{Int64}}, Tuple{UnitRange{Int64}}, true}

Stacktrace:
[1] push!(a::Vector{SubArray{Int64, 1, Arrow.Primitive{Int64, Vector{Int64}}, Tuple{UnitRange{Int64}}, true}}, item::Vector{Int64})
@ Base ./array.jl:1118
[2] _row_inserter!(df::DataFrame, loc::Int64, row::Tuple{String, Vector{Int64}, Int64, Int64, Int64, Int64, Int64, Int64, Int64, Int64, String, Bool, Bool, Bool, Vector{Int64}, Vector{Int64}, Vector{Int64}, String, String, Float64}, mode::Val{:push}, promote::Bool)
@ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/dataframe/insertion.jl:663
[3] push!(df::DataFrame, row::Tuple{String, Vector{Int64}, Int64, Int64, Int64, Int64, Int64, Int64, Int64, Int64, String, Bool, Bool, Bool, Vector{Int64}, Vector{Int64}, Vector{Int64}, String, String, Float64})
@ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/dataframe/insertion.jl:457
```

It's possible I'm doing something wrong; first time Arrow.jl user here.

Reproduce the example with Julia 1.10, Arrow 2.7.2, and DataFrames 1.6.1, starting at Arrow.write and Arrow.Table for Vector{Vector{T}} columns. Trace the resulting push! failure through DataFrames' insertion.jl:663 and determine the expected column behavior; done means the reported DataFrame insertion no longer raises the shown MethodError or the expected limitation is documented.

Written by the indexing model from the issue text.