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JuliaStats
StatsBase.jl
Julia2014–2022
JuliaStats / StatsBase.jl

StatsBase.jl

Basic statistics for Julia

5Distinct people
5Mentions
1Explicit recommenders
615GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Basic statistics for Julia

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

The core devs are in on the scrambling, too! This is now one of my favorite interactions on GitHub: https://github.com/JuliaStats/StatsBase.jl/pull/404

3JPLW used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

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.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year5 dated mentions

Observed mentions: 2014-12-29 21:47:58 UTC to 2022-06-23 17:02:20 UTC.

01232014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2022

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

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC303

What Hacker News says

5 sources
Well, out of the issues mentioned, the ones still open can be categorized as (1) aliasing problems with mutable vectors https://github.com/JuliaLang/julia/issues/39385 https://github.com/JuliaLang/julia/issues/39460 (2) not handling OffsetArrays correctly https://github.com/JuliaStats/StatsBase.jl/issues/646, https://github.com/JuliaStats/StatsBase.jl/issues/638, https://github.com/JuliaStats/Distributions.jl/issues/1265 https://github.com/JuliaStats/StatsBase.jl/issues/643 (3) bad interaction of buffering and I/O redirection https://github.com/JuliaLang/julia/issues/36069 (4) a type dispatch bug https://github.com/JuliaLang/julia/issues/41096 So if you avoid mutable vectors and OffsetArrays you should generally be fine. As far as the argument "Julia is really buggy so it's unusable", I think this can be made for any language - e.g. rand
Read the rest
is not random enough, Java's binary search algorithm had an overflow, etc. The fixed issues have tests added so they won't happen again. Maybe copying the test suites from libraries in other languages would have caught these issues earlier, but a new system will have more bugs than a mature system so some amount of bugginess is unavoidable.
In Julia ranks in the top 5 most loved programming languages for 2022
Most of these seem to be about packages in the ecosystem (which, after clicking through all links, actually almost all got fixed in a very timely manner, sometimes already in a newer version of the packages than the author was using), not about the language itself. Other than that, the message of this seems to be "newer software has bugs", which yes is a thing..? For example, the majority of issues referenced are specific to a single package, StatsBase.jl - which apparently was written before OffsetArrays.jl was a thing and thus is known to be incompatible: > Yes, lots of JuliaStats packages have been written before offset axes existed. Feel free to make a PR adding checks. https://github.com/JuliaStats/StatsBase.jl/issues/646#issuec... EDIT: Since this comment seems to gain some traction - title is editorialized, original is "Why I no lo
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nger recommend Julia".
In Correctness and composability bugs in the Julia ecosystem
I feel like people are perhaps a bit overly negative about the state of Julia's packages. Compared to other early-stage languages, I'd say our package ecosystem is vibrant and full of fantastic packages. Naturally perhaps they are more math/scientific focussed, so if you are looking for cutting-edge packages for web dev you won't find them yet (although there are packages!). See http://pkg.julialang.org/pulse.html, for example. We have over 470 packages in total that are registered, and on Julia 0.3 we have over 300 packages with tests that pass - and we run the tests in all registered packages every night. Some of my favorite packages (that I didn't make, of course :D) would include https://github.com/JuliaStats/Distributions.jl https://github.com/JuliaStats/StatsBase.jl https://github.com/pluskid/Mocha.jl (deep learning) https://github.
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com/stevengj/PyCall.jl The JuliaOpt stack of optimization packages (http://juliaopt.org) and then you get fun new ones like https://github.com/anthonyclays/RomanNumerals.jl
In Julia is awesome, but..

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