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Blog

Writing on statistical computing, reproducible research, and R

Writing on statistical computing, reproducible research, clinical-trial methodology, and open-source R software. Earlier posts are archived at focusonr.org.

Functional Plot Generation with purrr

r

data-visualization

I did not really know how to programmatically generate multiple plots from grouped data until I discovered purrr’s map2 and pmap functions – this post walks through the approach step by step using Palmer Penguins.

Setting Up Multi-Language Quarto Documents on macOS

quarto

r

python

julia

A practical guide to the configuration plumbing required to render a multi-language Quarto document from scratch on macOS.

Rapid Conversion of Draft R Scripts to Formal Rmd Reports

r

rmarkdown

reproducibility

I did not really know how to quickly convert a working R script into a presentable report until I discovered knitr::spin() and a few supporting workflows that changed how I share analytical results.

Install Linux Mint on a MacBook Air

linux

macos

r

python

workflow-construct

A practical guide to installing Linux Mint 22 on a 2016 MacBook Air, transforming aging Apple hardware into a functional data science workstation.

Provisioning AWS EC2 Instances: Console and CLI Methods

aws

shell

shiny

docker

Setting up an AWS EC2 instance from scratch, with two parallel paths: a console walkthrough for understanding the components, and four bash scripts for repeatable CLI automation.

Research Backup Architecture: Ongoing System and GitHub Archival

git

shell

macos

reproducibility

A unified treatment of research backup architecture: the three-tier ongoing system (automated Git pushes, cloud sync, and Time Machine) and the bulk GitHub archival procedure for migrating 400+ private repositories to local storage with verified backups and selective deletion.

Extending the R-Vim Workflow: LaTeX Integration and Dynamic Snippets

vim

r

python

workflow-construct

A complete configuration guide for the Vim-based R and LaTeX workflow: vimtex for LaTeX compilation, ALE for linting, UltiSnips for static snippet expansion, and UltiSnips Python interpolation for dynamic, parametric snippets.

Sharing R Code via Docker: R Markdown Reports and Shiny Applications

r

docker

rmarkdown

shiny

reproducibility

I did not really know how fragile sharing R code could be until my colleague spent an afternoon debugging missing packages, and I realised Docker could have prevented every single error – whether the output was a static PDF or a live Shiny app.

Migrating Off Dropbox: Beyond Dotfiles

workflow

sync

migration

dropbox

Post 24 establishes a portable dotfiles repository. This post extends the same goal to the rest of a single-user research workflow: project content, backup-pipeline source paths, and the append-only history files that Dropbox handles particularly badly. Frames the problem as three layers and walks through trade-offs for each.

A tiered CI strategy for zzcollab research compendia

ci

github-actions

reproducibility

zzcollab-compendia

renv

I did not realise how much my CI was lying to me until I added a single explicit failure check and watched five ‘passing’ projects turn honestly red. A workflow-style migration guide for zzcollab projects across four workspace types.

Setting up OBS for Live R Coding Screencasts

setup

obs

youtube

screencast

r

reproducibility

A reproducible workflow for producing short, focused screencasts of R data analysis using OBS Studio and YouTube. Includes installation, scene configuration, recording, editing, and a worked five-minute example based on the Palmer Penguins dataset.

From testthat to tinytest: Converting an R Package Test Suite

r

testing

tinytest

testthat

packaging

I did not really appreciate how much ceremony testthat carries until I rewrote a small package’s suite in tinytest and lost roughly two-thirds of the lines without losing any coverage.

A 55-Item Initiation Checklist for zzcollab Data Analyses

r

zzcollab-compendia

reproducibility

workflow

checklist

quarto

A clinical research collaborator emails a single CSV file with twelve columns, two hundred and eighty-seven rows, no codebook, and a promise of an updated extract ‘next week’. We walk through the fifty-five items that move that attachment from the inbox to a reproducible zzcollab compendium ready for archival.

Refactoring a Personal Toolbox: Scripts versus Shell Functions

shell

shell-and-git

Personal toolboxes accumulate helpers across years of small fixes: some end up as shell functions in ‘.zshrc’, some as scripts in ‘~/bin’, often with no consistent rule for which goes where. A principled split (function only when shell state must change, versioned script otherwise) removes hundreds of lines of logic from the average dotfile, makes every helper shellcheck-able, and reduces shell startup time.

Building a statistical computing textbook in the Age of AI

quarto

teaching

reproducibility

I did not really appreciate how much structural decision-making goes into a textbook until I tried to draft two at once, both under the ‘in the Age of AI’ framing.

A pocket terminal for your Linux laptop with ttyd and Tailscale

linux

shell

workflow-construct

A reproducible configuration for browser-based terminal access to a Linux laptop from a mobile device, using ttyd for the terminal emulation layer and Tailscale for authenticated network transport, with no public-internet exposure.

Dynamic Column Names in R: Seven Approaches Compared

r

metaprogramming

r-language

A comprehensive guide to adding columns with programmatically-generated names in R dataframes. Covers base R, tidyverse (classic and modern), data.table, collapse, rlang::inject(), and do.call patterns.

Updating an R Package: A Complete Development Workflow

r

package-development

git

I did not really understand the full lifecycle of modifying an R package until I had to push a feature branch through CI/CD and watch it either pass or fail on three operating systems. This post walks through the entire process.

Setting Up Neovim as a Data Science IDE

neovim

vim

r

python

I did not really know how much faster code editing could be until I switched from a mouse-driven IDE to Neovim’s modal, keyboard-centric workflow.

Reproducible Blog Posts with ZZCOLLAB: A Quarto Workflow

quarto

r

docker

reproducibility

zzcollab-compendia

I did not really appreciate how fragile technical blog posts are until one of my own stopped rendering six months after publication. This post documents the workflow I built to treat each blog post as a standalone ZZCOLLAB reproducible research project with Docker, renv, and CI/CD.

The Pipe Equivalence Myth: When `f() |> g()` Is Not the Same as `g(f())`

r

metaprogramming

r-language

Piping and nesting function calls are semantically different operations. A subtle bug in an expression- capturing wrapper reveals how R’s lazy evaluation interacts with the pipe operator.

Running ZZedc Independently for Clinical Research Data Management

clinical-trials

shiny

aws

reproducibility

I did not really know how achievable investigator independence in clinical data management was until I deployed ZZedc on a personal AWS instance and ran a pilot study without vendor involvement.

From Markdown to Blog Post: A ZZCOLLAB Conversion Workflow

quarto

zzcollab-compendia

reproducibility

A systematic workflow for converting standalone markdown documentation into professional blog posts using ZZCOLLAB symlinks and Quarto metadata.

Combining Observable JS and Shiny in a Single Quarto Document

quarto

shiny

javascript

r

data-visualization

I did not really know how difficult it would be to combine Observable JS and Shiny in one Quarto document until every data-loading approach I tried failed except fetching from a public URL.

Testing Data Analysis Workflows in R

r

testing

reproducibility

I did not really know how to systematically test a data analysis pipeline until I applied software engineering practices from testthat and assertr to my own research workflow.

Configuring Yabai as a Tiling Window Manager on macOS

macos

shell

I did not really know how much faster a tiling window manager could make my daily workflow until I configured yabai with keyboard shortcuts and stopped reaching for the mouse.

Writing a Simple Vim Plugin for REPL Interaction

vim

r

r-packages

I did not really know how Vim’s terminal API worked until I wrote a small plugin that sends code from an editing buffer to a running R session.

Prototyping a Shiny App with ChatGPT

r

shiny

I did not really know how effective ChatGPT could be as a prototyping partner until I iteratively built a modular Shiny app for Palmer Penguin exploration in three prompts.

A Mac Workflow for Tracking Daily Research Progress

shell

git

macos

I did not really know how to keep a consistent daily research log until I combined macOS dictation with ChatGPT summarization and a few short bash scripts. This post walks through the entire workflow from folder structure to searchable, version-controlled notes.

Clinical Trial Data Validation Across Languages and Tools

clinical-trials

data-cleaning

r

lua

javascript

I did not really understand how many layers of validation sit between a clinical trial data entry form and a reliable analysis dataset until I started mapping out EDC edit checks, open-source tools, and the possibility of generating JavaScript validation from a simple spreadsheet processed by Lua.

Palmer Penguins Part 5: Random Forest versus Linear Models

r

random-forest

machine-learning

model-selection

A head-to-head comparison reveals that a random forest outperforms the linear model by only two percentage points, prompting reflection on the interpretability-performance tradeoff.

Palmer Penguins Part 4: Model Diagnostics and Interpretation

r

regression

model-selection

Verifying regression model trustworthiness through systematic diagnostic checks on linearity, normality, and influence.

Palmer Penguins Part 3: Cross-Validation and Model Comparison

r

cross-validation

random-forest

machine-learning

penguins-arc

Testing whether regression models hold up on new data through ten-fold cross-validation and comparison against a random forest.

Palmer Penguins Part 2: Multiple Regression and Species Effects

r

regression

Adding species identity to the body mass prediction model causes R-squared to jump from 0.76 to 0.86, demonstrating the power of biological groupings in multiple regression.

Predictive Modeling of Penguin Body Mass

r

regression

data-visualization

Regression models on the Palmer Penguins dataset reveal how much species identity shapes morphometric relationships. Simpson’s Paradox emerges clearly, reversing an apparent correlation once species is accounted for.

Palmer Penguins Part 1: Exploratory Data Analysis and Simple Regression

r

regression

data-visualization

penguins-arc

An exploration of how a simple flipper measurement can reveal substantial information about penguin body mass through the Palmer Penguins dataset and simple linear regression.

Constructing a reproducible blog post using zzcollab tools

r

zzcollab-compendia

reproducibility

I didn’t really know much about [topic] until I tried to [implement/understand] it myself. Here’s what I learned along the way.