Unable to Convert Categorical Fields

[usmcamp0811]

Not to a be a thorn in your side but looks like I uncovered another issue. I was playing around some more with DataFrames and converted a few fields to the Categorical Type and then piped it into Voyager and got a similar error as this one. Its pretty much the same problem as issue #9 . I don't think its a super high priority issue but something to be aware of.

data: eeg-brain-wave-for-confusion

using Queryverse 

macro __str(x)
       :(Symbol($x))
end

# load some data into a dataframe
df = load("/home/mcamp/JuliaProjects/eeg-brain-wave-for-confusion/EEG_data.csv") |> DataFrame

cols = names(df)
cols[15] = _"UserDefinedLabel" 
cols[14] = _"PreDefinedLabel"
names!(df, cols) 

categorical!(df,:SubjectID)
categorical!(df,:UserDefinedLabel)
categorical!(df,:PreDefinedLabel)
categorical!(df,:VideoID)

df |> Voyager()

Retruns:

MethodError: Cannot `convert` an object of type Float64 to an object of type CategoricalValue{Float64,UInt32}
Closest candidates are:
  convert(::Type{T<:(Union{CategoricalString{R}, CategoricalValue{T,R} where T} where R)}, !Matched::T<:(Union{CategoricalString{R}, CategoricalValue{T,R} where T} where R)) where T<:(Union{CategoricalString{R}, CategoricalValue{T,R} where T} where R) at /home/mcamp/.julia/packages/CategoricalArrays/04bks/src/value.jl:65
  convert(::Type{S}, !Matched::T<:(Union{CategoricalString{R}, CategoricalValue{T,R} where T} where R)) where {S, T<:(Union{CategoricalString{R}, CategoricalValue{T,R} where T} where R)} at /home/mcamp/.julia/packages/CategoricalArrays/04bks/src/value.jl:66
  convert(::Type{T}, !Matched::T) where T at essentials.jl:154
  ...

Stacktrace:
 [1] setindex!(::Dict{Symbol,CategoricalValue{Float64,UInt32}}, ::Float64, ::Symbol) at ./dict.jl:381
 [2] Dict{Symbol,CategoricalValue{Float64,UInt32}}(::Base.Generator{Base.Iterators.Zip2{NTuple{15,Symbol},Tuple{CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32},Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32}}},getfield(DataVoyager, Symbol("##2#4"))}) at ./dict.jl:104
 [3] dict_with_eltype at ./abstractdict.jl:541 [inlined]
 [4] macro expansion at ./array.jl:591 [inlined]
 [5] dict_with_eltype at ./abstractdict.jl:546 [inlined]
 [6] Dict(::Base.Generator{Base.Iterators.Zip2{NTuple{15,Symbol},Tuple{CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32},Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32}}},getfield(DataVoyager, Symbol("##2#4"))}) at ./dict.jl:129
 [7] #1 at ./none:0 [inlined]
 [8] iterate at ./generator.jl:47 [inlined]
 [9] collect(::Base.Generator{TableTraitsUtils.TableIterator{NamedTuple{(:SubjectID, :VideoID, :Attention, :Mediation, :Raw, :Delta, :Theta, :Alpha1, :Alpha2, :Beta1, :Beta2, :Gamma1, :Gamma2, :PreDefinedLabel, :UserDefinedLabel),Tuple{CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32},Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64,CategoricalValue{Float64,UInt32},CategoricalValue{Float64,UInt32}}},Tuple{CategoricalArray{Float64,1,UInt32,Float64,CategoricalValue{Float64,UInt32},Union{}},CategoricalArray{Float64,1,UInt32,Float64,CategoricalValue{Float64,UInt32},Union{}},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},Array{Float64,1},CategoricalArray{Float64,1,UInt32,Float64,CategoricalValue{Float64,UInt32},Union{}},CategoricalArray{Float64,1,UInt32,Float64,CategoricalValue{Float64,UInt32},Union{}}}},getfield(DataVoyager, Symbol("##1#3"))}) at ./array.jl:619
 [10] (::Voyager)(::DataFrame) at /home/mcamp/.julia/packages/DataVoyager/h5fKO/src/DataVoyager.jl:36
 [11] |>(::DataFrame, ::Voyager) at ./operators.jl:813
 [12] top-level scope at In[18]:20