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Multithreaded package for working with tabular data in Julia

Results 26 InMemoryDatasets.jl issues
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Hi there, Would it be possible for you to create a discord server to answers simple questions about `InMemoryDatasets` and `DLMReader`? You can put its link on the first page.

decision

Many features has been added to `IMD` overtime, and I basically have added some docs about them here and there. Proofreading, adding more help, complete docstrings, ... are sort of...

documentation
enhancement
good first issue

https://github.com/sl-solution/InMemoryDatasets.jl/blob/4220d4bdc03e95098c498ed4012b6bee8fe50eb1/test/join.jl#L811 I cannot reproduce it, however, it must be checked - e.g. make sure that it is not related to data race. Perhaps, it is due to `cumsum!`??? The problem...

bug
help wanted

``` ds = Dataset(A = ["a", "b","a", "b"],B=[1,2,3,4]) julia> ds.A==ds[:,:A] true julia> typeof(ds.A) DatasetColumn{Dataset, Vector{Union{Missing, String}}} julia> typeof(ds[:,:A]) Vector{Union{Missing, String}} (alias for Array{Union{Missing, String}, 1}) julia> ds.A 4-element Vector{Union{Missing, String}}:...

I wonder if the result of the flatten function in these cases is the most expected one. Are there any contraindications to (or is this notoriously preferable rather than) treating...

bug
enhancement
decision

I don't explain the reason for the following differences ``` julia> modify(compare(ds[!, r"lim"], ds[!, Not(r"lim")], on = 1:3 .=> 1:3, eq = !isless), 1:3=>byrow(x->x.*1)) 6×4 Dataset Row │ a_lim=>a b_lim=>b...

Trying to follow some examples from the tutorial, I found different outputs than expected(as showed in the documentation). ``` julia> ds = Dataset(g = [2, 1, 1, 2, 2], x1_int...

We should check if can improve the performance of `sort` using other algorithms

enhancement
performance