I have a one dimensional array of the following type:
5001-element Array{Union{Float64, Missings.Missing},1}
I want to convert it into a pure Float64 array to be able to process it with the function Statsbase.crosscor . How can I achieve that?
Missing values should be replaced with NaN.
Thanks for your replies!
             
            
              
              
              
            
            
           
          
            
            
              Something like
v = [rand() > 0.90 ? missing : rand() for i in 1:10^4]
g(x) = x === missing ? NaN: x
g.(v)
perhaps?
             
            
              
              
              
            
            
           
          
            
            
              In 0.7 you can just do
replace(df[col], missing=>NaN)
It’ll even know to change the array type to Vector{Float64}, which I was impressed with.
             
            
              
              
              2 Likes
            
            
           
          
            
            
              Fixed a typo:
Works like a charm!
Thank you!
             
            
              
              
              1 Like