Rmarkdown Blogs

2/5/2026 • EN

Michael Toth

Michael Toth is a consulting data scientist and writer known for clear, practical guides to data visualization in R. His work focuses on ggplot, effective graph design, and helping data scientists communicate insights with impact.

Data Science R Programming Data Visualization

Michael Toth

20

2/1/2026 • EN

Tom Mock

Tom Mock’s blog focuses on R programming, data visualization, and reproducible research. He shares practical tutorials for RMarkdown, Quarto, tidyverse, and creative data presentation techniques.

r programming data visualization rmarkdown

Tom Mock

20

1/31/2026 • EN

Zoe Locke

Zoe Locke writes about the R programming ecosystem, covering package development, testing, data manipulation, and tips for R users at all levels. Her posts include practical advice, tutorials, and insights for R developers and data scientists.

R programming R packages data science

Zoe Locke

18

1/28/2026 • EN

kieran healy

Kieran Healy is a Professor of Sociology at Duke University, specializing in social networks, data visualization, and sociological theory. He is the author of several books, including The Ordinal Society and Data Visualization.

Sociology data visualization social networks

kieran healy

11

1/28/2026 • EN

Garrick Aden-Buie

Garrick Aden-Buie is a Software Engineer for Shiny at Posit (formerly RStudio), building tools with R, Shiny, and R Markdown to support data science workflows. He is also an educator and former data scientist with experience in health analytics and smart home research.

Shiny R development data science tools

Garrick Aden-Buie

19

1/28/2026 • EN

Christophe Dervieux

Christophe Dervieux is a software engineer at RStudio (Posit) working on the R Markdown ecosystem, including rmarkdown, knitr, blogdown, and bookdown. He shares tips and experiences with R, reproducible reporting, and open-source contributions.

R Markdown reproducible reporting open source R

Christophe Dervieux

7

1/28/2026 • EN

Andrew Heiss

Andrew Heiss is a researcher and educator focused on data visualization, causal inference, and applied statistics using R and Bayesian methods. He writes extensively about reproducible research, GIS, and analytical workflows, and teaches data science and social science methods.

data visualization causal inference R programming

Andrew Heiss

55

Rmarkdown Blogs

Michael Toth

Tom Mock

Zoe Locke

kieran healy

Garrick Aden-Buie

Christophe Dervieux

Andrew Heiss

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