Potpourri: Statistics #102
Jul 4, 2026
- Parameterized plots and reports with R and Quarto
- The Polars vs pandas difference nobody is talking about
- The brms Book: Applied Bayesian Regression Modelling Using R and Stan
- Tips for data entry in Excel
- TIL: dplyr::mutate()'s .keep argument
- xkcd and Data Science
- Positron vs RStudio - is it time to switch?
- Dataviz accessibility principles, demonstrated by the 2024 presidential election dashboards
- US Presidential Elections - A Bayesian Perspective
- Working with colours in R
- Misleading graph
- From Default Python Line Chart to Journal-Quality Infographics
- Modern Polars: A side-by-side comparison of the Polars and Pandas libraries
- Guide to comparing sample and population proportions with CPS data, both classically and Bayesianly
- Machine Learning in Production: From Models to Products
- Designing monochrome data visualisations
- Efficient Machine Learning with R: Low-Compute Predictive Modeling with tidymodels
- Visualizing Data Is An Art - We Should Treat It Like One
- Piping ggplot2 objects into plotly
- Beautiful Maps with R (I): Fishnets, Honeycombs and Pixels
- Beautiful Maps with R (II): Fun with flags
- Beautiful Maps with R (III): Patterns and hatched maps
- Beautiful Maps with R (IV): Fun with flags revisited
- Beautiful Maps with R (V): Point densities
- Easy geom recipes
- Large Language Model tools for R
- Defense Against Dishonest Charts
- Data Frames as Vectors of Rows
- How to use a histogram as a legend in {ggplot2}
- The Best Way to Use Text Embeddings Portably is With Parquet and Polars
- Awesome Polars
- Understand geom_bar and its statistical transformations
- Data Viz Showcase
- The guide to gradients in R and ggplot2
- Python Developer Tooling Handbook
- Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
- R, DuckDB and Me
- R Graphics Cookbook
- Sketchy waffle charts in R
- An Introduction to Bayesian Multi-Membership Models Using brms
- Fonts in R
- When good pseudorandom numbers go bad
- tidyverse functions you might not know about
- Speed up your data science and scientific computing code
- A step-by-step chart makeover
- Refactoring code with flir
- The 80/20 Guide to R You Wish You Read Years Ago
- Spatial machine learning with R: caret, tidymodels, and mlr3
- From lab to real life: How your Shiny application can survive its users
- A friendly guide to choosing a chart type
- An Introduction to Behavior-Driven Development in R
- Learn Stan with brms, Part I
- Pretty base plots
- Learn Stan with brms, Part II
- Learn Stan with brms, Part III
- Within-person factorial experiments, log(normal) reaction-time data
- Animated Maps with {ggplot2} and {gganimate}
- Simulating and Visualising the Central Limit Theorem
- A Visual Exploration of Gaussian Processes
- Introduction to Julia for R users
- Patterns, Predictions, and Actions: A story about machine learning
- Visualization for Social Data Science
- The Art of Data Visualization with ggplot2
- Exploring {ggplot2}'s Geoms and Stats
- Joining strings with missing data together in R
- ggplot2 styling
- Mapply: When You Need to Iterate Over Multiple Inputs
- Testing with {testthat}
- Neon Ghosts with ggplot2
- An Introduction to Writing Your Own ggplot2 Geoms
- Jarl: just another R linter
- Ways to load / attach packages in R
- Things you may or you may not know in ggplot2
- Saloni's guide to data visualization
- Broken Chart: discover 9 visualization alternatives
- Three levels to compose R functions
- Doing Bayesian Data Analysis in brms and the tidyverse
- How to create a more accessible line chart
- Hello Data Science: A Friendly Introduction with Applications
- Deep Analysis with Polars: Transforming and Visualizing Data for Insights
- Trying out dplyr 1.2.0
- Introduction to building (better) R packages
- Intro to PyTorch: Easy to follow, visual introduction
- Modern Julia Workflows
- Why I don't use {tidymodels}
- Interactive beeswarm charts in R
- How to Estimate a Mean, and What It Means for Science
- Bayesian statistics for confused data scientists
- Introducing ggauto: automating better charts
- Models as Prediction Machines: How to Convert Confusing Coefficients Into Clear Quantities
- Statistical Computing using R and Python
- Are you ready for R? A Workbook for R for Political Science and Beyond
- Five ggplot2 functions I wish I'd known about earlier
- Friends don't let friends run moderated cross-country regressions
- tufte-viz Claude Code skill — Edward Tufte data visualization principles
- How to create a more accessible line chart
- 11 Test Smells That Make Your Tests Lie to You
- The Data Analyst's Guide to Cause and Effect
- The annotated PyTorch training loop
- Binary logistic regression in R
- The 4 Layers of Testing Every R Package Needs