posts – Agile Data Science

Visual Studio Code: Toolkit for Data Scientists

programming

TL;DR Visual Studio Code offers a complete toolkit for data science work. Its language-agnostic design supports Python, R, and other languages through extensions. GitHub…

Maciej Nasinski

GLM Residuals Distributions

statistics

TL;DR Explains residual analysis in generalized linear models (GLMs), particularly logistic (binary outcomes) and Poisson (count outcomes). Using R, we clearly introduce…

Maciej Nasinski

Curse of Dimensionality: Lessons from the U.S. Air Force Cockpit Design

statistics

TL;DR: In the late 1940s, the U.S. Air Force faced a potentially life-threatening challenge. Despite state-of-the-art technology in their fighter planes, pilots were…

Maciej Nasinski

Open Source: Given enough eyeballs, all bugs are shallow

programming

TL:DR Open source is software (and sometimes hardware or data) whose source code is publicly accessible. Anyone can view, modify, and distribute it, which fosters…

Maciej Nasinski

Unlocking the Power of Mermaid Diagrams

programming

TL;DR Mermaid allows anyone to define and render professional-quality diagrams quickly. Whether you are a developer documenting a process, a project manager outlining…

Maciej Nasinski

WebAssembly: A True Web Revolution

programming

TL;DR: WebAssembly (WASM) revolutionizes web development by enabling near-native performance for web applications written in languages like Rust, C++, R, and Python. With…

Maciej Nasinski

Python Enhancement Proposals (PEPs)

pythonprogramming

TL;DR Python Enhancement Proposals (PEPs) are the official mechanisms for proposing, discussing, and implementing new features or changes in the Python programming language.…

Maciej Nasinski

Object-Oriented Programming for Data Science Developers [In-Depth]

programming

in-depth

TL;DR For developers creating their own data science libraries or packages, Object-Oriented Programming (OOP) is fundamental for structuring and maintaining complex…

Maciej Nasinski

Containers for Data Scientists [In-Depth]

programming

in-depth

TL;DR: Containers provide reproducible, secure, and portable environments for data scientists and statistical programmers. While tools like renv for R and requirements.txt…

Maciej Nasinski

Conjugate Priors: Harnessing Closed-Form Solutions in Bayesian Inference

statistics

TL;DR: Conjugate priors are special prior distributions in Bayesian inference that, when combined with a given likelihood, yield a posterior in the same family as the prior.…

Maciej Nasinski

Bernstein–von Mises: Bridging Bayesian and Frequentist Worlds

statistics

TL;DR Bernstein–von Mises Theorem: Under certain regularity conditions and large sample sizes, the Bayesian posterior for a parameter converges to a normal distribution…

Maciej Nasinski

Celebrating a Classic: “How R Searches and Finds Stuff” by Suraj Gupta

rprogramming

TL;DR The blog post “How R Searches and Finds Stuff” by Suraj Gupta, is a comprehensive guide that delves into the internals of R’s search mechanism. Despite being over 12…

Maciej Nasinski

Graph Database and GQL

programming

TL;DR Graph databases have emerged as a crucial technology for managing and analyzing data that is highly interconnected. Unlike traditional relational databases that store…

Maciej Nasinski

Scrum: Just a Framework, Agile: A General Philosophy

programming

TL;DR In the world of project management, Agile has become a guiding light for many organizations. Often, there’s a misconception that Agile is synonymous with Scrum.…

Maciej Nasinski

Exploring the Tinyverse: A New Standard in R Package Development

rprogramming

TL;DR The “tinyverse” represents a modern approach in the R programming community, advocating for the creation of packages with minimal dependencies. This movement addresses…

Maciej Nasinski

Stack Overflow Developer Survey Insights for Strategic Tech Planning

programming

TL;DR The annual Stack Overflow Developer Surveys have become a cornerstone for those looking to gain a competitive edge in the tech industry. These surveys provide a…

Maciej Nasinski

ggcall: Transparent R Packages with ggplot2

rprogramming

TL;DR Two functions in ggplot2 are overwritten (ggplot and +) to achieve code transparency and reproducibility when ggplot2 is used inside a function.
It is believed that…

Maciej Nasinski

GitHub Codespaces

programming

TL;DR GitHub Codespaces is a cloud-based development environment that simplifies and enhances the software development workflow. GitHub Codespaces provides fully configured…

Maciej Nasinski

GitHub Student Developer Pack: Learn to ship software like a pro

programming

TL;DR The GitHub Student Pack offers students free access to a suite of powerful development tools, including Codespaces, GitHub Copilot, GitLens Pro GitKraken and much…

Maciej Nasinski

Pre-commit: A framework for managing and maintaining multi-language pre-commit hooks

programming

TL;DR Pre-commit hooks are an essential tool for maintaining high code quality in software development, especially for R and Python projects. These hooks automatically run…

Maciej Nasinski

Analyzing the Kasa Romana Lottery with Knapsack Algorithm [Updated]

knapsack

rprogramming

TL;DR If you want to design the perfect lottery where participants believe they have a chance to win but can never actually do so, you’ll need the expertise of a skilled…

Maciej Nasinski

Moving Beyond P-Values in Scientific Research: Insights from the ASA Statement and Frank Harrell

p-value

statistics

TL;DR ASA suggests that researchers should report effect sizes, confidence intervals, and other measures of uncertainty alongside p-values.

Maciej Nasinski

Why Git is Here to Stay

git

TL;DR Git remains a staple in the programming community and is likely to continue being so for a long time.

Maciej Nasinski