A tutorial for R users on mastering data wrangling in 5 progressive levels, using the dplyr package and the Ames housing dataset.
A comparison of the native Base R pipe (|>) and the {magrittr} pipe (%>%), covering their syntax, strictness, and use cases for data analysis.
A tutorial on using R to parse Apple Music XML data and create personalized listening statistics similar to Spotify Wrapped.
A tutorial on creating interactive, production-grade tables in R using the reactable and reactablefmtr packages.
A tutorial on creating calendar heatmap plots using ggplot2 in R to visualize time-series data like flight frequencies.
A tutorial on enhancing line charts using ggplot in R, covering themes, colors, labels, and direct labeling techniques.
A tutorial on the six most fundamental R functions for data cleaning, using the tidyverse and palmerpenguins dataset.
Using R simulations to calculate birthday probabilities instead of complex probability math, with code examples.
A tutorial using custom animations to visually explain how dplyr's mutate(), summarize(), group_by(), and ungroup() functions work in R.
Explains key causal inference estimands (ATE, ATT, ATU) and how to calculate them using observational data, with a focus on R and the potential outcomes framework.
A statistical analysis using R and Bayesian modeling to convert Aragorn's Dúnedan age from Lord of the Rings into equivalent human years, based on Tolkien's writings.
A technical tutorial on using R to read, analyze, and visualize your downloaded Twitter archive data, including tweets, likes, and ad history.
A tutorial demonstrating how to use the R `slider` package for rolling window analysis, using NFL quarterback performance data as an example.
A personal review of 2020 focusing on the growth of the #TidyTuesday data visualization project in the R community, with code and analysis.
A technical tutorial on using R and inverse probability weighting to handle time-series panel data for causal inference with marginal structural models.
A technical guide on creating and customizing bullet chart variants using R and ggplot2, including code examples and comparisons of different approaches.
A professor details the curriculum and practical challenges of teaching an undergraduate 'Data Science Practice' course, covering data prep, predictive models, and tools like R and keras.
A technical tutorial on creating hexagon maps (hexmaps) for visualizing New Zealand District Health Board data using the R programming language and the DHBins package.
Explains why the rimu R package avoids tidyverse for type safety with multiple-response data, using a custom S3 class approach.
Explores the psychological reasons behind heated debates in data science, like R vs. Python, and why they are often unproductive.
