This page summarizes the features supported by different Parquet implementations. Note: If you find out of date information, please help us improve the accuracy of this page by opening an issue or sub...

TLDR; small, local models are a good instrument for measuring what a harness costs an agent. an API is only as good as its outputs’ specificity, parsimony, and truthfulness. obvious code repair...

YouTube video by OST – Ostschweizer Fachhochschule

Quick tips about tools and techniques for fast iteration when developing Haskell

OverviewWe present dataframe-learn, a machine learning library where the output of training models is symbolic expressions. We first motivate why symbolic mo...

Curated reactive Haskell notebooks.

Curated reactive Haskell notebooks.

A while ago I saw the article Which languages are most token efficient. The article was largely discredited since it didn’t have a clear methodology. Unfortunately, I haven’t come up with one yet but ...

Every dataframe library ships with hundreds of operations. pandas alone has over 200 methods on a DataFrame. Is pivot different from melt? Is apply different from map? What about transform, agg, apply...

Some years ago I came across an issue in the Frames repo that mentioned a blog post titled “Why pandas feels clunky when coming from R.” The article showed a side-by-side of simple data exploration in...

Explore this conversation and more from the dataengineering community

This post is the convergence of two ideas that have been floating in my head for about a year. Can we learn messy stochastic models and use algorithmic/algebraic tools to rein in model complexity to make models interpretable?

Every dataframe library ships with hundreds of operations. pandas alone has over 200 methods on a DataFrame. Is pivot different from melt? Is apply different from map? What about transform, agg, apply...

It’s been roughly two years of work on this and I think things are in a good enough state that it’s worth calling this v1. Features Typed dataframes We got there eventually and I think we got there i...

Overview

Sabela is a reactive notebook environment for Haskell. The name is derived from the Ndebele word meaning “to respond.” The project has two purposes. Firstly, it is an attempt to design and create a mo...

A lot of tabular modeling gets easier the moment you stumble onto the right derived quantity. Not something mysterious or “deep.” It’s usually something you can name: a ratio that turns two raw column...

Exploratory data analysis (EDA) isn’t just for data scientists. Anyone that uses a system that emits data can benefit from the tools of EDA. And since charit...

Persistent database integration for the dataframe library

Hello everyone! The Haskell Foundation is reviving @taylorfausak’s State of Haskell Survey. It’s been a few years and so we’re doing it a bit differently, but the plan is to start doing this yearly a...