Convert Int64 array to Int8 in Julia gives InexactError: trunc(Int8, -9223372036854775808) - type-conversion

Question

I try to convert a part of an julia df from Int64 to Int8.
input:
array = convert(Array{Int8} , array );
output:
InexactError: trunc(Int8, -9223372036854775808)
Stacktrace:
[1] throw_inexacterror(f::Symbol, #unused#::Type{Int8}, val::Int64)
# Core ./boot.jl:612
[2] checked_trunc_sint
# ./boot.jl:634 [inlined]
[3] toInt8
# ./boot.jl:649 [inlined]
[4] Int8
# ./boot.jl:759 [inlined]
[5] convert
# ./number.jl:7 [inlined]
[6] setindex!
# ./array.jl:903 [inlined]
[7] _unsafe_copyto!(dest::Vector{Int8}, doffs::Int64, src::Vector{Int64}, soffs::Int64, n::Int64)
# Base ./array.jl:253
[8] unsafe_copyto!
# ./array.jl:307 [inlined]
[9] _copyto_impl!
# ./array.jl:331 [inlined]
[10] copyto!
# ./array.jl:317 [inlined]
[11] copyto!
# ./array.jl:343 [inlined]
[12] copyto_axcheck!
# ./abstractarray.jl:1104 [inlined]
[13] Vector{Int8}(x::Vector{Int64})
# Base ./array.jl:563
[14] Array
# ./boot.jl:482 [inlined]
[15] convert(#unused#::Type{Array{Int8}}, a::Vector{Int64})
# Base ./array.jl:554
[16] top-level scope
# In[62]:1
[17] eval
# ./boot.jl:373 [inlined]
[18] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
# Base ./loading.jl:1196
Also:
Input:
maximum(array)
output:
11
So the bigges value of this is under 255 which is the max size of Int8.
thanks,
Bene

Answer 1

While the maximum value in your data is 11, the minimum value in your data is -9223372036854775808, also known as typemin(Int64), which cannot be converted to Int8 since that type can only represent values from -128 to 127.

Answer 2

Sometimes the typemin value in the array is used to indicate a null value or a missing value. This isn't the best practice in Julia, but it's possible your data source is using the value this way.
Say you have an array arr:
julia> arr = [1, 2, typemin(Int), 4]
4-element Vector{Int64}:
1
2
-9223372036854775808
4
If the typemin value is supposed to indicate missing data, you can do:
julia> [n == typemin(Int) ? missing : Int8(n) for n in arr]
4-element Vector{Union{Missing, Int8}}:
1
2
missing
4
Or if it's supposed to indicate null/invalid data, you can use nothing instead of missing above.