urbanr
🏙️ A package for wrangling urban area data in R
🏙️ A package for wrangling urban area data in R
Published in F1000 Research, 2024
Recommended citation: Savonen et al. (2024). "Motivation, inclusivity, and realism should drive data science education." F1000 Research. 12, 1-22.
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Published in Environmental Data Science, 2024
Recommended citation: Oliver et al. (2024). "Opening a conversation on responsible environmental data science in the age of large language models." Environmental Data Science. 3, 1-17.
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Published in PLOS Computational Biology, 2024
Recommended citation: Hoffman and Wright (2024). "Ten simple rules for teaching an introduction to R." PLOS Computational Biology. 20(5), 1-9.
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Published in Bioinformatics, 2024
Recommended citation: Afiaz et al. (2024). "Best practices to evaluate the impact of biomedical research software—metric collection beyond citations." Bioinformatics. 40(8), 1-11.
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Published in Nature Ecology & Evolution, 2024
Recommended citation: Cocciardi et al. (2024). "The value of long-term ecological research for evolutionary insights." Nature Ecology & Evolution. 8(9), 1584–1592.
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Published in F1000 Research, 2025
Recommended citation: Isaac et al. (2025). "Insights into the Datasets, Tools, and Training Needs of the AnVIL Community: 2024." F1000 Research. 14, 1-23.
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Published in Nature Genetics, 2025
Recommended citation: The BioDIGS Consortium (2025). "Unearthing soil biodiversity through collaborative genomic research and education." Nature Genetics. 58, 3-8.
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Graduate course, Johns Hopkins University, Biostatistics, 2025
I have taught this tidyverse-focused introduction to R programming eight times since 2021.