dplyr VS nx

Compare dplyr vs nx and see what are their differences.


Multi-dimensional arrays (tensors) and numerical definitions for Elixir (by elixir-nx)
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dplyr nx
40 36
4,670 2,491
0.8% 1.8%
7.1 9.3
4 days ago 3 days ago
R Elixir
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Posts with mentions or reviews of dplyr. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-15.


Posts with mentions or reviews of nx. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-25.
  • Unpacking Elixir: Concurrency
    9 projects | news.ycombinator.com | 25 Aug 2023
    Does nx not work for you? https://github.com/elixir-nx/nx/tree/main/nx#readme
  • A LiveView Is a Process
    5 projects | news.ycombinator.com | 16 Jun 2023
    It is historically not great at number computing. This is being addressed by a relatively new project called Nx. https://github.com/elixir-nx/nx

    It is not the right choice for CPU intensive tasks like graphics, HFT, etc. Some companies have used Rust to write native extensions for those kinds of problems. https://discord.com/blog/using-rust-to-scale-elixir-for-11-m...

  • How does Elixir stack up to Julia in the future of writing machine-learning software?
    3 projects | /r/Julia | 27 May 2023
  • Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R
    7 projects | news.ycombinator.com | 14 Apr 2023
    José from the Livebook team. I don't think I can make a pitch because I have limited Python/R experience to use as reference.

    My suggestion is for you to give it a try for a day or two and see what you think. I am pretty sure you will find weak spots and I would be very happy to hear any feedback you may have. You can find my email on my GitHub profile (same username).

    In general we have grown a lot since the Numerical Elixir effort started two years ago. Here are the main building blocks:

    * Nx (https://github.com/elixir-nx/nx/tree/main/nx#readme): equivalent to Numpy, deeply inspired by JAX. Runs on both CPU and GPU via Google XLA (also used by JAX/Tensorflow) and supports tensor serving out of the box

    * Axon (https://github.com/elixir-nx/axon): Nx-powered neural networks

    * Bumblebee (https://github.com/elixir-nx/bumblebee): Equivalent to HuggingFace Transformers. We have implemented several models and that's what powers the Machine Learning integration in Livebook (see the announcement for more info: https://news.livebook.dev/announcing-bumblebee-gpt2-stable-d...)

    * Explorer (https://github.com/elixir-nx/explorer): Series and DataFrames, as per this thread.

    * Scholar (https://github.com/elixir-nx/scholar): Nx-based traditional Machine Learning. This one is the most recent effort of them all. We are treading the same path as scikit-learn but quite early on. However, because we are built on Nx, everything is derivable, GPU-ready, distributable, etc.

    Regarding visualization, we have "smart cells" for VegaLite and MapLibre, similar to how we did "Data Transformations" in the video above. They help you get started with your visualizations and you can jump deep into the code if necessary.

    I hope this helps!

  • Elixir and Rust is a good mix
    10 projects | news.ycombinator.com | 13 Apr 2023
    > I guess, why not use Rust entirely instead of as a FFI into Elixir or other backend language?

    Because Rust brings none of the benefits of the BEAM ecosystem to the table.

    I was an early Elixir adopter, not working currently as an Elixir developer, but I have deployed one of the largest Elixir applications for a private company in my country.

    I know it has limits, but the language itself is only a small part of the whole.

    Take ML, Jose Valim and Sean Moriarity have studied the problem, made a plan to tackle it and started solving it piece by piece [1] in a tightly integrated manner, it feels natural, as if Elixir always had those capabilities in a way that no other language does and to put the icing on the cake the community released Livebook [2] to interactively explore code and use the new tools in the simplest way possible, something that Python notebooks only dream of being capable of, after a decade of progress

    That's not to say that Elixir is superior as a language, but that the ecosystem is flourishing and the community is able to extract the 100% of the benefits from the tools and create new marvellously crafted ones, that push the limits forward every time, in such a simple manner, that it looks like magic.

    And going back to Rust, you can write Rust if you need speed or for whatever reason you feel it's the right tool for the job, it's totally integrated [3][4], again in a way that many other languages can only dream of, and it's in fact the reason I've learned Rust in the first place.

    The opposite is not true, if you write Rust, you write Rust, and that's it. You can't take advantage of the many features the BEAM offers, OTP, hot code reloading, full inspection of running systems, distribution, scalability, fault tolerance, soft real time etc. etc. etc.

    But of course if you don't see any advantage in them, it means you probably don't need them (one other option is that you still don't know you want them :] ). In that case Rust is as good as any other language, but for a backend, even though I gently despise it, Java (or Kotlin) might be a better option.

    [1] https://github.com/elixir-nx/nx https://github.com/elixir-nx/axon

    [2] https://livebook.dev/

    [3] https://github.com/rusterlium/rustler

    [4] https://dashbit.co/blog/rustler-precompiled

  • Distributed² Machine Learning Notebooks with Elixir and Livebook
    7 projects | news.ycombinator.com | 11 Apr 2023
    (including docs and tests!): https://github.com/elixir-nx/nx/pull/1090

    I'll be glad to answer questions about Nx or anything from Livebook's launch week!

  • Why Python keeps growing, explained
    7 projects | news.ycombinator.com | 3 Mar 2023
    I think that experiment is taking shape with Elixir:


  • Does Nx use a Metal in the Backend ?
    2 projects | /r/elixir | 19 Jan 2023
    However the issue here at Nx https://github.com/elixir-nx/nx/issues/490 is already closed.
  • Do I need to use Elixir from Go perspective?
    5 projects | /r/elixir | 9 Jan 2023
    Outside of that, Elixir can be used for data pipelines, audio-video processing, and it is making inroads on Machine Learning with projects like Livebook, Nx, and Bumblebee.
  • Elixir – HUGE Release Coming Soon
    3 projects | news.ycombinator.com | 7 Dec 2022

What are some alternatives?

When comparing dplyr and nx you can also consider the following projects:

worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob

Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications

Rustler - Safe Rust bridge for creating Erlang NIF functions

gleam - ⭐️ A friendly language for building type-safe, scalable systems!

ggplot2 - An implementation of the Grammar of Graphics in R

axon - Nx-powered Neural Networks

explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir

explorer - An open source block explorer

rmarkdown - Dynamic Documents for R

fib - Performance Benchmark of top Github languages

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

meander - Tools for transparent data transformation