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Comment by enriquto | Hacker News Reader

this is not really an issue, as long as you ignore the julia plotting capabilities; which should have never been there anyway. You can easily dump your numbers (and functions) on a text file and gnuplot them.

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Uhh no. I do a lot of data analysis and if I have to dump stuff into text files every time I want to visualize something quickly then I'm going to go mental.

Simple plots take a fraction of a second in Python/R/Matlab. I feel like many people don't realize how crucial this is. Sub-second plotting makes working with data interactive. If it takes more than 5 seconds to produce simple plots, that's no longer interactive. Imagine if your debugger took half a minute to show you the value of a variable while trying to find a complex bug. You'd start pulling your hair out.

If in Julia it takes me half a minute at least (dumping to text file, reading it in somewhere else and then plotting it), Julia is going to remain firmly in the "check this language again in 2 years time if the plotting story has become sensible yet".

It would be great if it were quicker. But right now, interactive use is pretty good, like 5ms for a simple plot. It's calling julia from the command line, and thus starting cold, which is more than 5s.

That is just a really terrible way to do things and I have no idea why you would excuse it like that. Typical workflow if you use the Plots.jl package is to wait half a minute for the package to load in the REPL and then stay in the same REPL for your workflow so that you won't have to reload the package.

What I do is wait one second for the RCall.jl package to load and then use R's ggplot2 library to plot. Works really well, especially since I am really familiar with ggplot2.

I do not use the REPL, I call julia scripts from elsewhere, and then I want to recover the data out of julia, and text files are perfectly appropriate (a few thousand numbers). Then julia plotting capabilities are suboptimal with respect to specialized plotting software like gnuplot. I would really prefer if julia did not have any plotting stuff.

That's not typical workflow for the majority of data scientists. And saying you prefer Julia not have any plotting stuff sounds really really dumb to be frank.

Agreed. As a data scientist myself, I can't imagine Julia getting much "mindshare" among us with the JIT experience it has. Perhaps we're not the real target audience for Julia? But if that's the case then adoption will likely be slow, and limited to only very niche applications and roles. For Julia to really become the next big thing (and solve the damn two language problem), it needs to be an effective solution for data scientists and machine learning engineers--and right now, it just isn't.

I do machine learning and computer vision in python, statistical analysis, plotting, and anything to do with dataframes in R, and computational stuff, network science, and almost everything else in julia. I would like to switch my data analysis stuff to julia but waiting for libraries and functions to load is just too frustrating when I'm doing things interactively. I'm hoping Julia will have a good machine learning, computer vision, and data science environment in the future and it is looking like it will. But for now, it is not an easy environment to work with in these applications and you'd need some fairly specific needs to justifiably use Julia here. But the thing is that when you do have relatively esoteric things to do in these applications, it is much easier to do them in Julia.

Not a data scientist, sorry, just a mathematician

Also pretty much into the unix philosophy whereby tools should do only one thing and do it well.

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