Min-Woong you could use convert, it works with NAs and you still get an
error for free if conversion is not possible:
julia> df = DataFrame(x = @data [1,2,3, NA, typemax(Int8)])
5x1 DataFrames.DataFrame
| Row | x |
|-----|-----|
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
| 4 | NA |
| 5 | 127 |
julia> eltype(df[:x])
Int64
julia> df[:x] = convert(DataArray{Int8, 1}, df[:x]);
julia> eltype(df[:x])
Int8
julia> df = DataFrame(x = @data [1,2,3, NA, typemax(Int8) + 1])
5x1 DataFrames.DataFrame
| Row | x |
|-----|-----|
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
| 4 | NA |
| 5 | 128 |
julia> eltype(df[:x])
Int64
julia> df[:x] = convert(DataArray{Int8, 1}, df[:x]);
ERROR: InexactError()
in copy! at abstractarray.jl:302
El jueves, 24 de diciembre de 2015, 5:02:14 (UTC-6), Min-Woong Sohn
escribió:
>
> I want to reduce the amount of memory used by a dataframe that has lots of
> binary variables. What is the best way to achieve this? For example, how
> can I convert a variable from Int64 to Int8 in a dataframe.
>
> Thanks
>
