NimData

DataFrame API written in Nim, enabling fast out-of-core data processing

Data & Databases

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3Mentions

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342GitHub stars

REPOSITORY AT A GLANCE

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What it is

DataFrame API written in Nim, enabling fast out-of-core data processing

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

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Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2017-04-20 21:36:28 UTC to 2021-02-24 15:57:52 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Comments
2017	2017-01-01 00:00:00 UTC	2018-01-01 00:00:00 UTC	2	2
2018	2018-01-01 00:00:00 UTC	2019-01-01 00:00:00 UTC	0	0
2019	2019-01-01 00:00:00 UTC	2020-01-01 00:00:00 UTC	0	0
2020	2020-01-01 00:00:00 UTC	2021-01-01 00:00:00 UTC	0	0
2021	2021-01-01 00:00:00 UTC	2022-01-01 00:00:00 UTC	1	1

What Hacker News says

3 sources

cb321·Feb 24, 2021

There is NimData [1] and ggplotnim [2] and Arraymancer [3]. Also, neovim works well with the alaviss plugin [4], though it's not quite a full IDE. Most Nim coders use VS. [1] https://github.com/bluenote10/NimData [2] https://github.com/Vindaar/ggplotnim [3] https://github.com/mratsim/Arraymancer [4] https://github.com/alaviss/nim.nvim

In Nim versions 1.4.4 and 1.2.10

FridgeSeal·Apr 28, 2017

Sorry I only just saw this message: yeah, turns out there's 2: * https://github.com/qqtop/nimdataframe And * https://github.com/bluenote10/NimData

In Nim programming language

muraiki·Apr 20, 2017

I started out learning programming using Python and gradually came to prefer strongly typed languages. I'm aware of 1 1/2 options for doing this kind of work in a strongly typed language that isn't C++: Option 1: F# or C# with the Deedle[1] library. Deedle provides series and dataframe classes, along with various stats functions. I believe that there are also some vis tools. Type providers in F# allow you to specify a data source, such as a CSV or database, and then not only infer the types but also give you intellisense autocompletion. See the F# guide for data science[2] for more info. Option 1.5: I hesitate to recommend the following, because there's simply not much here yet, but there is a dataframe library[3] for Nim[4]. Nim is a strongly typed language with a Python-like syntax which compiles to C and is apparently quite fast. It ha

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s multiple options for garbage collection but also supports manual memory management. It offers lisp-like macros for implementing DSLs, which the dataframe library I mentioned uses quite a bit. The main problems with Nim are of course the lack of libraries and the need for a notebook-like environment such as Jupyter, which are certainly big problems indeed. But I think that Nim is something to look out for over the next few years. As much as I like Deedle and F#'s features, I've personally decided to abandon the use of Microsoft technologies due to their many user-unfriendly actions regarding Windows 10 and privacy. I don't fault anyone else for using Deedle, though, because it is a nice tool. This is just a personal decision of mine. [1] http://bluemountaincapital.github.io/Deedle/ [2] http://fsharp.org/guides/data-science/ [3] https://github.com/bluenote10/NimData [4] https://nim-lang.org

In New IPython release drops Python 2.7 support