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fix NaNtoMissing #116

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fix NaNtoMissing #116

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7 changes: 1 addition & 6 deletions src/fit_dataframe.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,6 @@
# REVIEW THIS IN LIGHT OF NEW DATAFRAMES
# ========================================

import Base: isnan
import DataFrames: DataFrame, ncol, convert


Expand Down Expand Up @@ -269,16 +268,12 @@ function expand_categoricals!(df::DataFrame,categoricals::Array)
return expand_categoricals!(df, categoricalidxs)
end

# convert NaNs to NAs
# isnan(x::NAtype) = false
isnan(x::AbstractString) = false
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this was type-piracy.
Fixed the problem that it was avoiding via adding isa Number check below

isnan(x::Union{T, Nothing}) where T = isnan(x.value)
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This was a bad find and replace from a previous PR that replaced Nullable with Union{Nothing, T}
It was always nonsense.
idk why it wasn't breaking tests earlier


# same functionality as above.
function NaNs_to_Missing!(df::DataFrame)
m,n = size(df)
for j=1:n
df[!,j] = [ismissing(df[i,j]) || isnan(df[i,j]) ? missing : value for (i,value) in enumerate(df[:,j])];
df[!,j] = [(value isa Number && isnan(value)) ? missing : value for value in df[!,j]];
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this is just a bit simpler we only need the value, and adds the isa Number check

end
return df
end
Expand Down