– A detailed guide to colors in data vis style guides

– parlscot: An R package to download Scottish Parliamentary data

– France 2022: How to predict an election

– peacesciencer: Tools and Data for Quantitative Peace Science

– Left-Right Placements of GB Westminster Constituencies in 2021

– Effects of Causes and Causes of Effects

– A Critical Perspective on Effect Sizes

– Codebook Package Comparison

– Micronumerosity

– A Journey to gghdr

– Sports Data Analysis and Visualization

– Creating APIs for Data Science With plumber

– RMarkdown is great

– Do cluster robust standard errors give false positives on cross-level interactions?

– Neural Networks and Deep Learning

– Web scraping in R

– How to Correctly Use Lists in R?

– Linear Regression

– Groundhog 2.0: Further addressing the threat R poses to reproducible research

– Violent Incident Information from News Articles

– Predicting Goals Using the Winning Odds

– Uncommon advice on becoming a data scientist in the public interest

– The cursed Morgan Stanley Covid-19 visualization

– Stop aggregating away the signal in your data

– loopurrr: Translate purrr functions into regular for loops

– PRISMA2020: An R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis

– Wikidata for data journalism

– Frustration: One Year With R

– Teaching R in a Kinder, Gentler, More Effective Manner: Use Base-R, Not the Tidyverse

– Handbook of Regression Modeling in People Analytics

– Using Amazon S3 with R

– Deep Learning Is Hitting a Wall

– R Without Statistics

– subs2vec: Word embeddings from subtitles in 55 languages

– Statistical Tools for Causal Inference

– A Dataset Documenting Representations of Machine Vision Technologies in Artworks, Games and Narratives

– R Packages for Analyzing Spatial Data: A Comparative Case Study with Areal Data

– A couple of visualizations from ggforce

– What does it mean to have a low R-squared ? A warning about misleading interpretation

– highcharter a11y talk

– Self-documenting plots in ggplot2

– CAST: Caret Applications for Spatio-Temporal models

– Checking the inputs of your R functions

– Challenges in Package Management

– Leading Data Science Teams

– Coding style, coding etiquette

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