I’ve been trying out the BayesNets.jl package. I would like to learn the structure of a bayesian network using a small number of Bool variables in a DataFrame.

First, I set the parameters of the search

```
data = CSV.read("/training.csv", truestrings=["TRUE"], falsestrings=["FALSE"])
vars = [:X1, :X2, :X3, :X4, :X5, :X6]
parameters = K2GraphSearch(vars, DiscreteCPD, max_n_parents=2)
```

Then, I try running the structure search (using a dataframe)

```
fit(BayesNets.DiscreteBayesNet, data, parameters)
```

But I get this exception:

```
ERROR: MethodError: no method matching infer_number_of_instantiations(::CSV.Column2{Bool,Bool})
Closest candidates are:
infer_number_of_instantiations(::AbstractArray{I,1}) where I<:Int64 at /Users/---/.julia/packages/BayesNets/XwVs4/src/CPDs/utils.jl:62
Stacktrace:
[1] fit(::Type{CategoricalCPD{DiscreteNonParametric{Int64,Float64,Base.OneTo{Int64},Array{Float64,1}}}}, ::DataFrame, ::Symbol, ::Array{Symbol,1}) at /Users/----/.julia/packages/BayesNets/XwVs4/src/CPDs/categorical_cpd.jl:128
[2] fit(::Type{BayesNet{CategoricalCPD{DiscreteNonParametric{Int64,Float64,Base.OneTo{Int64},Array{Float64,1}}}}}, ::DataFrame, ::K2GraphSearch) at /Users/----/.julia/packages/BayesNets/XwVs4/src/learning.jl:254
[3] top-level scope at /Users/---/Workspace/Julia_EDA/SEBayes.jl:12
```

I’m having trouble understand what the error is. Any ideas?