I have data-frame contain some missing values, I want to replace all the missing values with the mean of LoanAmount column
df[ismissing.(df.LoanAmount),:LoanAmount]= floor(mean(skipmissing(df.LoanAmount)))
but when I am running above code i am getting
MethodError: no method matching setindex!(::DataFrame, ::Float64, ::BitArray{1}, ::Symbol)
Use skipmissing e.g.:
mean(skipmissing(df.LoanAmount))
Answer to the second, edited question: you should broadcast the assignment using the dot operator (.) as in the example below:
julia> df = DataFrame(col=rand([missing;1:3],10))
10×1 DataFrame
│ Row │ col │
│ │ Int64? │
├─────┼─────────┤
│ 1 │ missing │
│ 2 │ 3 │
│ 3 │ 2 │
│ 4 │ 2 │
│ 5 │ missing │
│ 6 │ missing │
│ 7 │ missing │
│ 8 │ 3 │
│ 9 │ 1 │
│ 10 │ 3 │
julia> df[ismissing.(df.col),:col] .= floor(mean(skipmissing(df.col)));
julia> df
10×1 DataFrame
│ Row │ col │
│ │ Int64? │
├─────┼────────┤
│ 1 │ 2 │
│ 2 │ 3 │
│ 3 │ 2 │
│ 4 │ 2 │
│ 5 │ 2 │
│ 6 │ 2 │
│ 7 │ 2 │
│ 8 │ 3 │
│ 9 │ 1 │
│ 10 │ 3 │
yet another option is to use Impute.jl as suggested by Bogumil:
Impute.fill(df;value=(x)->floor(mean(x)))
I found this one also, when we need to replace with mean
replace!(df.col,missing => floor(mean(skipmissing(df[!,:col]))))
when we need to replace with mode
replace!(df.col,missing => mode(skipmissing(df[!,:col])))