dplyr
nx
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dplyr | nx | |
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40 | 36 | |
4,645 | 2,455 | |
0.6% | 1.2% | |
7.4 | 9.4 | |
14 days ago | 12 days ago | |
R | Elixir | |
GNU General Public License v3.0 or later | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dplyr
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Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
That's great feedback, thanks!
This tool definitely comes from a place of personal need - beyond just handling large files, I've also never really gelled well with the Excel/Google Sheet model of changing data in place as if you were editing text. I'm a Data Scientist and always preferred the chained data transforms you see in things like dplyr (https://dplyr.tidyverse.org/) or Polars (https://pola.rs/) and I feel this tool maps very closely to the chained model.
Also, thank you for the feature requests! Those would all be very useful - we'll put them on the roadmap.
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IS it possible for a R package to set an R option that only affects that package?
There's an example of how to use zzz.R with a .onload() function to set options in the dplyr code base: https://github.com/tidyverse/dplyr/blob/bbcfe99e29fe737d456b0d7adc33d3c445a32d9d/R/zzz.r
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Calculation within a data table by calling on specific values in two columns
Look at the tidyverse, especially the case_when or mutate functions.
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PSA: You don't need fancy stuff to do good work.
Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.
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Creating data frame
It looks like your syntax is wrong. I think you’re trying to calculate a new variables in your data frame, or alter an existing column in a data frame. Have a look at the select() function in this reference for the proper syntax to use. https://dplyr.tidyverse.org/ Does that help?
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I'm designing a shirt for a friend, it has 4 embroidered images of things they like/do. One thing is coding, they use R... I'm wondering two things. 1) What's a good image or piece of code or something that I should use? and 2) should I even add it to the design the shirt?
A lot of populat libraries have their own logos. Maybe one of them would be good. Check out dplyr for example: https://dplyr.tidyverse.org/
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Anyone use Python for statistics, particularly DOE or QA/QC? What are your thoughts?
I hope you give it a try when you get a chance: https://dplyr.tidyverse.org/
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Rstudio tidyverse help!
You can read up on the dplyr-verbs here, which I strongly suggest for your exam! In the code examples, you can simply click on any function you don't understand and it will take you directly to the documentation. Good Luck!
- Beginner question
- osdc-2023-assignment1
nx
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Unpacking Elixir: Concurrency
Does nx not work for you? https://github.com/elixir-nx/nx/tree/main/nx#readme
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A LiveView Is a Process
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?
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Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R
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!
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Elixir and Rust is a good mix
> 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
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Distributed² Machine Learning Notebooks with Elixir and Livebook
(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!
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Why Python keeps growing, explained
I think that experiment is taking shape with Elixir:
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Does Nx use a Metal in the Backend ?
However the issue here at Nx https://github.com/elixir-nx/nx/issues/490 is already closed.
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Do I need to use Elixir from Go perspective?
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
What are some alternatives?
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
clojerl - Clojure for the Erlang VM (unofficial)