Bogumił Kamiński
Bogumił Kamiński
The benchmarks.jl fails now (seems to use https://github.com/rohitvarkey/BenchmarkHelper.jl which is not imported).
Given: ``` julia> using CategoricalArrays julia> x = repeat(1:10^6, 100); julia> @time y = categorical(x); 13.253178 seconds (102.82 M allocations: 3.645 GiB, 8.79% gc time) julia> @time y = categorical(x);...
I find the following behavior inconsistent. Is it on purpose? ``` julia> using CategoricalArrays julia> x = categorical([1,2,3], ordered=true) 3-element CategoricalArrays.CategoricalArray{Int64,1,UInt32}: 1 2 3 julia> x[3] = 10 ERROR: cannot...
@nalimilan Currently: ``` x = categorical([1,2,3]) y = deepcopy(x) x.pool == y.pool ``` produces `false` because for `CategoricalPool` the operation `==` is not defined and falls back to `===`. Is...
Currently `SubArray` of `CategoricalArray` is not recognized as `CategoricalArray`. The consequence is that the code that wants to handle both has to use: ``` Union{CategoricalArray, SubArray{T, N,
In https://github.com/bkamins/Julia-DataFrames-Tutorial/blob/master/04_loadsave.ipynb, cell [38] writing a CSV file is strangely slow. Especially in comparison to writing writing `objecttable` which is much faster.
See https://stackoverflow.com/questions/65584387/julia-csv-write-very-memory-inefficient/65585017?noredirect=1#comment115971096_65585017. The reason is https://github.com/JuliaData/CSV.jl/blob/main/src/write.jl#L422. Maybe we could keep an `IOBuffer` that would be reused by consecutive calls to `Dates.format` to reduce allocations?
The request to handle fixed with format pops up frequently. Here are the major points of the functionality (this is an ideal state - not all has to be implemented...
When outputting floats when writing a CSV file it would be nice to allow users to control what kind of notation should be used (maybe allow to pass a formatter)....
I am not sure who in JuliaData is maintaining JuliaDB, but it requires a release as the current release holds back PooledArrays.jl to a very old version.