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Move df macro here? #3336
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i think this is fine, as i believe tables Api is lightweight. I agree that dataframes are quite common |
Notably, this would not be breaking |
Don't we need it to be breaking? Otherwise, the current StatsPlots release would be compatible with a new Version of Plots that exports the |
I think it would in general be nice to move stuff from StatsPlots that does not require an additional dependency in Plots. Most notably, I am sometimes annoyed to require StatsPlots for
I think groupedbar would be nice to have in Plots and maybe also boxplot, not sure about the others. |
I usually find the need in ecdf, but never understood if it is a really complex recipe to be included in Plots |
Oh it might make sense with a breaking release because of StatsPlots - what I meant is that it should not break any user's workflow. Agree on groupedbar and boxplot, and for the others maybe they do belong (and are best documented) in StatsPlots - so essentially I agree with you Daniel. |
A bit late to the party, but I also agree with @daschw. Only extra comment is that after JuliaStats/KernelDensity.jl#84 loading time of KernelDensity is a bit better, so maybe it is not out of the question to port recipes that rely on it (in practice, For reference, on my machine and julia 1.6 julia> @time using Plots
4.435312 seconds (6.89 M allocations: 498.039 MiB, 4.78% gc time, 0.78% compilation time)
julia> @time using KernelDensity
1.358977 seconds (2.20 M allocations: 147.740 MiB, 8.93% gc time)
julia> @time using Distributions # this one would be for free as it is a KernelDensity dep, but maybe distribution recipes belong in StatsPlots
0.000669 seconds (251 allocations: 16.328 KiB) |
Maybe use this change to think of a better name, e.g. |
I think this has been discussed several times on StatsPlots, but let's move it here. My suggestion is to simply move the
@df
macro from StatsPlots to here. Having data in dataframes is a common use case for plotting, and the placement on the macro in StatsPlots is a legacy from julia 0.5 and before, where DataFrames was a massive dependency. With the Tables interface this issue is resolved. @daschw @pieverThe text was updated successfully, but these errors were encountered: