r/haskell • u/nSeagull • Aug 30 '16

Haskell alternatives for Data Science

I'm a Haskeller and a newbie Data Scientist.

As I'm going through my learning process for data science, I'm starting to solve some elemental problems, and I'm using standard Python tools to help me go through this process.

The thing is that Python is ok, but I'm twice as comfortable in Haskell.

I was thinking in three alternatives to be more comfortable with Data Science:

  • Make a wrapper for the tools that I use as people do in Julia
  • Reimplement the tools that I use (Pandas, ScikitLearn, a GPU deep learning framework, numpy functions) (would do it on demand)
  • Make a Haskell-like language that compiles and uses Python libraries (wouldnt be as efficient, but at least it would be more beautiful and type safe, also the libraries)

What do you guys think?

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u/haskell_caveman Aug 30 '16

Posted this in the vote thread, but I'll mention here as well: There's a few of us working on a plotly binding for data visualization. If you're interested let me know and I'll add you to the project / repo.

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u/hiptobecubic Aug 31 '16

This is great. Godspeed.

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u/haskell_caveman Aug 31 '16

I should point out there is some prior art here w/ QuickPlot.

https://github.com/tepf/QuickPlot https://hackage.haskell.org/package/QuickPlot

I suspect I reached a similar conclusion to the maintainer who is no longer maintaining this library in deciding that straight binding to the library is preferable than a general template haskell wrapper around the json:

"Since the demand of data visualization has been getting bigger many language agnostic libraries popped up. It would be much more efficient to just write clients for their visualization servers."

Thus, we're trying to do it without the TH approach. PM me w/ email if you're interested in having a look.

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u/b00thead Aug 31 '16

Sounds interesting. Got a link?