Top all-time · #13636
Ritchie Vink
Personal blog · ritchievink.com/blogdataprogramming
Ritchie Vink's personal blog at ritchievink.com covers data and programming. Since 2019, 5 different Hacker News readers have linked it 6 times, most often “I wrote one of the fastest DataFrame libraries”. The last post was in 2021, but the archive is still widely read.
Too few sampled comments (3) to say how often HN recommends it.?
Why HN links it
HN readers link this blog for a Python recreation of Facebook's Prophet time-series model using PyMC, and for benchmarks of DataFrame library performance, including data.table comparisons.
Summarised by Claude from a sample of 3 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Most-linked posts?
- I wrote one of the fastest DataFrame libraries2 people · 2 mentions · first linked 2021-03-14
- /blog/2018/10/09/build-facebooks-prophet-in-pymc3-bayesian-time-series-analyis-with-generalized-additive-models/2 people · 2 mentions · first linked 2019-11-09
What Hacker News says?
A good explanation for prophet that made it click for me was its recreation with python in pymc https://www.ritchievink.com/blog/2018/10/09/build-facebooks-...
Comment linking /blog/2018/10/09/build-facebooks-prophet-in-pymc3-bayesian-time-series-analyis-with-generalized-additive-models/
on “Time Series Prediction – A short introduction for pragmatists”Submitted I wrote one of the fastest DataFrame libraries as a story · 389 points
HN discussion"Massively better performance" is a bit misleading: Julia is only massively better at certain workflows. The fastest data.frame library in ALL interpreted languages is consistently data.table, which is R. For in-memory data analysis, Julia will have to offer more than performance to win over statisticians/researchers. Benchmarks: https://www.ritchievink.com/blog/2021/02/28/i-wrote-one-of-t...
Comment linking /blog/2021/02/28/i-wrote-one-of-the-fastest-dataframe-libraries/
on “Julia Computing raises $24M Series A”Submitted Polars v0.15.0: Fastest DataFrame library written in Rust as a story · 2 points
HN discussionLike most models its data dependent. Had quite a lot of success (was paid) using it on data with multi-seasonality (daily plus seasonal trend) with regressors and change points, where there is not a lot of other options. As its a General Additive Model you can decompose the prediction into parts put them in front of a non-technical user for validation i.e. show effect of daily seasonality, yearly, holidays and regre…
Comment linking /blog/2018/10/09/build-facebooks-prophet-in-pymc3-bayesian-time-series-analyis-with-generalized-additive-models/
on “Is Facebook's “Prophet” the time-series Messiah or just a naughty boy?”Submitted Polars v0.15.0: Fastest DataFrame library written in Rust as a story · 1 points
HN discussion