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Hadley Wickham
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Hadley Alexander Wickham (born 14 October 1979) is a New Zealand statistician known for his work on open-source software for the R statistical programming environment. He is the chief scientist at Posit PBC and an adjunct professor of statistics at the University of Auckland, Stanford University, and Rice University. His work includes the data visualisation system ggplot2 and the tidyverse, a collection of R packages for data science based on the concept of tidy data.
Key Information
Early life and education
[edit]Wickham was born in Hamilton, New Zealand. He received a bachelor's degree in human biology and a master's degree in statistics at the University of Auckland in 1999–2004 and his PhD at Iowa State University in 2008, supervised by Di Cook and Heike Hofmann.[2][4]
His sister, Charlotte Wickham, is also a statistician, data scientist and educator. She taught in the Statistics Department at Oregon State University between 2011 and 2022,[5] and currently works for Posit PBC on the developer relations team.[6] She holds a first-class honours bachelor of science degree in Statistics from University of Auckland and a PhD in statistics from University of California, Berkeley.[7]
Career
[edit]Wickham is the chief scientist at Posit PBC (formerly RStudio PBC)[8] and an adjunct professor of statistics at the University of Auckland, Stanford University, and Rice University.[9][10][11]
He is a prominent and active member of the R user community, and has developed several notable and widely used packages including ggplot2, plyr, dplyr and reshape2.[11][12] Wickham's data analysis packages for R are collectively known as the tidyverse.[13] According to Wickham's tidy data approach, each variable should be a column, each observation should be a row, and each type of observational unit should be a table.[14]
Honors and awards
[edit]In 2006 he was awarded the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualisation.[15] Wickham was named a Fellow by the American Statistical Association in 2015 for "pivotal contributions to statistical practice through innovative and pioneering research in statistical graphics and computing".[16] Wickham was awarded the international COPSS Presidents' Award in 2019 for "influential work in statistical computing, visualisation, graphics, and data analysis" including "making statistical thinking and computing accessible to a large audience".[17]
Publications
[edit]Wickham's publications[1] include:
- Wickham, Hadley; Grolemund, Garrett (2017). R for Data Science : Import, Tidy, Transform, Visualize, and Model Data. Sebastopol, CA: O'Reilly Media. ISBN 978-1491910399. OCLC 968213225.
- Wickham, Hadley (2015). R Packages. Sebastopol, CA: O'Reilly Media, Inc. ISBN 978-1491910597.
- Wickham, Hadley (2014). Advanced R. New York: Chapman & Hall/CRC The R Series. ISBN 978-1466586963.
- Wickham, Hadley (2011). "The split-apply-combine strategy for data analysis". Journal of Statistical Software. 40 (1): 1–29. doi:10.18637/jss.v040.i01.
- Wickham, Hadley (2010). "A layered grammar of graphics". Journal of Computational and Graphical Statistics. 19 (1): 3–28. doi:10.1198/jcgs.2009.07098. S2CID 58971746.
- Wickham, Hadley (2010). "stringr: modern, consistent string processing". The R Journal. 2 (2): 3–28. doi:10.32614/RJ-2010-012.
- Wickham, Hadley (2009). ggplot2: Elegant Graphics for Data Analysis (Use R!). New York: Springer. ISBN 978-0387981406.[3]
- Wickham, Hadley (2007). "Reshaping data with the reshape package". Journal of Statistical Software. 21 (12): 1–20. doi:10.18637/jss.v021.i12.
References
[edit]- ^ a b Hadley Wickham publications indexed by Google Scholar
- ^ a b Hadley Wickham at the Mathematics Genealogy Project
- ^ a b Wickham, Hadley (2011). "ggplot2". Wiley Interdisciplinary Reviews: Computational Statistics. 3 (2): 180–185. doi:10.1002/wics.147. ISSN 1939-5108. S2CID 247702774.
- ^ Wickham, Hadley Alexander (2008). Practical tools for exploring data and models. iastate.edu (PhD). Iowa State University. doi:10.31274/rtd-180813-16852. OCLC 247410260. ProQuest 194000416. Retrieved 2019-02-14.
- ^ "Teaching". cwick.co.nz. Retrieved 2025-04-22.
- ^ "Charlotte Wickham". cwick.co.nz. Retrieved 2025-04-22.
- ^ "Charlotte Wickham | Department of Statistics". stat.oregonstate.edu. 2024-10-18. Retrieved 2025-04-22.
- ^ "Hadley Wickham". RStudio. Retrieved 2023-05-05.
- ^ "University of Auckland". Retrieved 2017-09-03.
- ^ "Hadley Wickham's Profile - Stanford Profiles". Retrieved 2017-09-03. [dead link]
- ^ a b "About - RStudio". Retrieved 2014-08-13.
- ^ "Top 100 R Packages for 2013 (Jan-May)!". R-statistics blog. 13 June 2013. Retrieved 2014-08-12.
- ^ "Welcome to the Tidyverse". Revolution Analytics. Retrieved 2016-09-21.
- ^ Wickham, Hadley (2014). "Tidy Data". Journal of Statistical Software. 59 (10). doi:10.18637/jss.v059.i10.
- ^ "John Chambers Award Past winners". ASA Sections on Statistical Computing, Statistical Graphics. Archived from the original on 2017-07-31. Retrieved 2014-08-12.
- ^ "ASA names 62 fellows" (PDF). American Statistical Association. Archived from the original (PDF) on 4 March 2016. Retrieved 14 November 2015.
- ^ "Kiwi wins prestigious international statistics award for his outstanding contributions to the profession". 26 October 2010. Retrieved 1 August 2019.
External links
[edit]- On the web
- Interviews
- Interview Archived 2023-02-01 at the Wayback Machine by Datascience.LA at UseR! 2014
- Interview by Yixuan Qiu (2013)
- Interview by Models are
- Talks and presentations
- Speaker Hadley Wickham Strata 2014 - O'Reilly Conferences, February 11 - 13, 2014, Santa Clara, CA Archived 2014-02-23 at the Wayback Machine
- Interview at Strata 2014 Illuminating and Wrong
- Ihaka Lecture Series 2017: Expressing yourself with R
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Hadley Wickham
View on Grokipediafrom Grokipedia
Early life and education
Early life
Hadley Wickham was born in 1979 in Hamilton, New Zealand.[13][14] He grew up in a family with strong ties to statistics and academia; his father, Brian Wickham, earned a PhD in animal breeding from Cornell University, which influenced the household's emphasis on quantitative fields.[14][15] Wickham has a younger sister, Charlotte Wickham, who is also a statistician and data scientist currently working as a Developer Educator at Posit PBC.[3] At age 15, while in high school, Wickham took his first job developing Microsoft Access databases to document database structures, a task that introduced him to practical data management.[14][15] This early work, inspired partly by his father's professional environment, sparked his interest in computing, as he experimented with tools like Microsoft Office on the family's early home computers.[15] Through these experiences, Wickham began exploring concepts in data organization and manipulation, laying the groundwork for his later focus on statistics.[14]Formal education
Wickham earned a Bachelor of Human Biology with First Class Honours from the University of Auckland in 1999.[16][5] He then completed a Bachelor of Science in Statistics and Computer Science with First Class Honours from the University of Auckland in 2002.[16][5] This degree built on his early interest in computing developed during his teenage years, providing a foundation in both statistical methods and programming that would inform his later work.[17] He continued his studies at the University of Auckland, completing a Master of Science in Statistics with First Class Honours in 2004.[16] Wickham then pursued doctoral studies in the United States, earning a PhD in Statistics from Iowa State University in 2008.[16] His dissertation, titled "Practical tools for exploring data and models," was supervised by Di Cook and Heike Hofmann and emphasized techniques in exploratory data analysis and visualization to support statistical modeling.[18][6]Professional career
Academic positions
Wickham served as Assistant Professor of Statistics at Rice University from 2008 to 2012.[16] During this period, he taught undergraduate and graduate courses focused on data analysis and visualization, including Statistical Computing and Graphics (Stat 405), Mathematical Statistics and Probability (Stat 310), and Data Visualisation (Stat 645).[16] These courses emphasized practical skills in statistical programming, graphical methods, and exploratory data techniques, often incorporating R for hands-on instruction.[16] As part of his academic research at Rice, Wickham developed early R packages to support data analysis and visualization workflows.[19] Following his assistant professorship, Wickham became an adjunct professor at Rice University in 2013, a position he continues to hold.[16] He also serves as an adjunct professor in the Institute for Computational and Mathematical Engineering at Stanford University (since approximately 2014) and as Honorary Professor of Statistics at the University of Auckland (ongoing).[20][21] These roles involve occasional teaching, supervision, and collaboration on data science initiatives.[19] In 2012, Wickham transitioned to a full-time industry position at Posit PBC while maintaining these academic affiliations.[7]Roles at Posit PBC
Hadley Wickham joined RStudio in 2012, becoming Chief Scientist in 2013, a role in which he focused on advancing data science tools and methodologies within the organization.[9] In this capacity, he led the development team responsible for the tidyverse, a collection of integrated packages designed to streamline data science workflows by emphasizing consistent grammar and principles for data manipulation, visualization, and modeling.[3] Following RStudio's rebranding to Posit PBC in 2022, Wickham continued serving as Chief Scientist, guiding the company's efforts to support open-source ecosystems for reproducible and efficient data analysis across programming languages like R and Python.[22] His leadership at Posit has emphasized building computational and cognitive tools that enhance data wrangling and exploratory analysis, fostering collaborative environments for data professionals.[3] Wickham relocated to Houston, Texas, earlier in his career and currently resides there with his husband and dogs, integrating his personal life with his remote-friendly industry responsibilities at Posit.[3] Alongside this executive role, he maintains adjunct academic positions at institutions such as Stanford University and Rice University.[3]Open-source contributions
Hadley Wickham pioneered the "tidy data" philosophy in 2014, introducing a standardized approach to organizing datasets for easier manipulation, modeling, and visualization in statistical computing. This framework emphasizes structuring data such that each variable forms a column, each observation forms a row, and each type of observational unit forms a table, addressing common inconsistencies in raw data formats to streamline data wrangling and analysis workflows. Wickham founded the tidyverse in the mid-2010s as a cohesive collection of R packages designed to implement and extend the tidy data principles, providing data scientists with consistent tools for data import, tidying, transformation, and visualization.[23] He has since maintained leadership over its development, collaborating with a team to ensure the ecosystem evolves with user needs and promotes unified design principles like shared data structures and intuitive function composition.[23] His role as Chief Scientist at Posit PBC has facilitated this ongoing maintenance by integrating tidyverse development into broader open-source initiatives.[3] Through numerous blogs, talks, and educational resources, Wickham has advocated for reproducible research and best practices in statistical computing, emphasizing tools like R Markdown to integrate code, results, and narrative for transparent workflows.[12] He stresses the importance of version control, documentation, and modular code to enable others to verify and extend analyses, influencing community standards for reliability in data science.[24]Recognition
Awards
Hadley Wickham received the John M. Chambers Statistical Software Award in 2006 from the American Statistical Association for his early work on extensions to lattice graphics, specifically through the development of the reshape and ggplot packages, which advanced practical tools for data reshaping and visualization in R.[25][26] Wickham was awarded the 2019 COPSS Presidents' Award, considered the highest honor in the field of statistics and often dubbed the "Nobel Prize of Statistics," for his transformative impact on data science tools through influential work in statistical computing, visualization, graphics, and data analysis.[27][10] In 2025, he received the ASA Statistical Computing and Graphics Award for his profound influence on statistical computing, visualization, and data analysis, particularly through significant contributions to open-source software in R.[28][29]Fellowships and memberships
Wickham has been a member of the R Foundation for Statistical Computing since 2014, where he contributes to the governance and strategic direction of the R programming language and its ecosystem.[30] As an ordinary member elected by the foundation's general assembly, he participates in decisions on funding, standards, and community initiatives that support open-source statistical computing.[31] In 2015, Wickham was elected a Fellow of the American Statistical Association, an honor recognizing his sustained and pivotal contributions to statistical practice through innovative software tools for data analysis, visualization, and reshaping.[32] This fellowship highlights his role in advancing accessible computational methods within the statistical community. Wickham holds ongoing adjunct professorships at several institutions, including Stanford University in the Institute for Computational and Mathematical Engineering, Rice University in the Department of Statistics, and the University of Auckland.[33][34][35] These positions enable him to mentor students, deliver lectures, and collaborate on research without full-time administrative duties, fostering connections between industry and academia in data science.Publications and software
Books
Hadley Wickham has authored or co-authored several influential books on R programming and data science, emphasizing practical methodologies, best practices, and innovative workflows that have shaped the field's pedagogy and adoption.[36] These works, published primarily with major academic and technical presses, have collectively amassed tens of thousands of citations, underscoring their role in advancing computational statistics and reproducible research.[36] His first major book, ggplot2: Elegant Graphics for Data Analysis, published in 2009 by Springer, introduces the grammar of graphics paradigm implemented in the ggplot2 package, providing a systematic framework for creating complex visualizations from data.[37] This foundational text has been cited over 87,000 times, influencing data visualization practices across disciplines by promoting layered, declarative approaches to plotting that separate data representation from aesthetic mapping.[36] In Advanced R, first published in 2014 by Chapman & Hall/CRC and updated in a second edition in 2019, Wickham delves into the internals of the R language, covering functional programming, metaprogramming, and performance optimization techniques to help programmers write more efficient and maintainable code.[38] The book, cited approximately 587 times, serves as a key resource for intermediate R users seeking deeper mastery, with examples drawn from real-world programming challenges.[36] Co-authored with Jennifer Bryan, R Packages (O'Reilly, 2015; second edition 2023) offers a comprehensive guide to developing, testing, and distributing R packages, including tools for documentation, version control, and automation using devtools and related workflows.[39] Cited over 426 times, it has empowered countless developers to contribute to the Comprehensive R Archive Network (CRAN), standardizing package creation and enhancing the ecosystem's scalability.[36] Finally, R for Data Science, co-authored with Mine Çetinkaya-Rundel and Garrett Grolemund (O'Reilly, 2017; second edition 2023), introduces the tidyverse suite of packages through iterative workflows for data import, tidying, transformation, and visualization, emphasizing literate programming with R Markdown.[40] With around 1,743 citations, this book has become a cornerstone for data science education, promoting "tidy" data principles that facilitate collaborative and reproducible analysis.[36]Key R packages
Hadley Wickham developed ggplot2 in 2005 during his PhD at Iowa State University as an implementation of Leland Wilkinson's The Grammar of Graphics, enabling declarative specifications of complex visualizations through layered components like data, aesthetics, geoms, and scales.[8] This approach allows users to build plots incrementally using function composition, later refined with the+ operator for readability, addressing limitations in base R and lattice graphics for exploratory data analysis.[41] By 2025, ggplot2 had amassed over 172 million downloads from CRAN as of November 2025, reflecting its widespread adoption as the standard for R data visualization in fields like statistics, data science, and academia.[42]
In 2014, Wickham released dplyr, a package providing a grammar of data manipulation through intuitive verbs that simplify common operations on data frames, such as filtering rows, adding or modifying columns, and aggregating summaries.[43] Key functions include filter() for subsetting based on conditions, mutate() for creating new variables from existing ones, and summarise() (often paired with group_by()) for computing summaries like means or counts across groups, all optimized for speed and inspired by SQL while integrating the pipe operator %>% for chaining operations. This design promotes readable, composable code for data wrangling, and by 2025, dplyr had exceeded 134.5 million CRAN downloads as of November 2025, establishing it as a cornerstone of modern R workflows.[42]
tidyr, also introduced by Wickham in 2014, focuses on reshaping messy datasets into tidy format—where each variable forms a column, each observation a row, and each cell a single value—to facilitate analysis and modeling.[44] Central functions like pivot_longer() convert wide data (multiple columns per variable) to long format for easier manipulation, while pivot_wider() performs the reverse to spread values into columns, building on earlier tools like gather() and spread() with improved flexibility for handling nested or hierarchical data. Evolving from Wickham's initial reshape package, tidyr supports rectangling operations to flatten complex structures, and it had garnered over 83 million CRAN downloads as of November 2025, underscoring its essential role in data preparation.[8][42]
The tidyverse meta-package, released in 2016 and named in 2016, integrates Wickham's core tools—including ggplot2, dplyr, tidyr, readr (for importing data), purrr (for functional programming), tibble (for enhanced data frames), stringr (for strings), and forcats (for factors)—into a cohesive ecosystem that enforces consistent syntax, data structures, and principles for end-to-end data science pipelines.[45] Users install and load all components via a single library(tidyverse) command, promoting interoperability and reducing friction in workflows from import to visualization, as detailed in Wickham's instructional texts. This unified approach has driven the tidyverse's dominance in R, with its packages collectively powering much of contemporary data analysis.[8]