- > There is now a DataFrame.Typed API that tracks the entire schema of the dataframe - column names, misapplied operations etc are now compile time failures and you can easily move between exploratory and pipeline work.
This makes complex dashboards so much easier to build, because in Python you have to test everything in the dashboard to make sure a change to a common dataset didn’t break anything.
Is there a good web dashboard library like streamlit for Haskell I wonder?
by brightball
1 subcomments
- If anybody is reading this and would like to submit a talk on it or Haskell itself to the Carolina Code Conference, please do so. Our call for speakers is open until the end of March and I've been hoping to get a Haskell talk in for the last couple of years.
https://blog.carolina.codes/p/call-for-speakers-2026-is-open
by whateveracct
0 subcomment
- And packed in here is more than Dataframe.
DataHaskell in general is revived and improving on multiple fronts. Exciting stuff!
by mark_l_watson
1 subcomments
- This looks so cool, just put it on top of my todo list. My Haskell skills are mediocre but I love the language. I get by with a subset of the language.
Strong typing and data science seems like a good combination.
- I feel like I've been waiting for this to mature for a decade. I love that the vision has been realized despite the enthusiasm for functional programming languages cooling off somewhat.
by hambandit
1 subcomments
- I learned some haskell as my hobby language a few years back. It was very cool and forced me to think about programming differently (and finally grok recursion). It never felt like a good language for data analysis to me though (maybe that's cause this library wasn't around? lol). This isn't meant a criticism of this library, instead, I'm curious the use cases the author, if you're around or a user, has in mind. Congrats on the v1 release!
by october8140
4 subcomments
- 1.0.0.0.0.0.0.0
- why choose an overlapping name with pandas dataframe?
- Is what?
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