Trends

Top trending packages by downloads from CRAN

Statistics

Analysis

Trending R packages reveal a strong focus on advanced statistical modeling and analysis. Several packages address specific needs within this domain, including network meta-analysis (ssifs), generalized additive models (gam, evgam), and functional time series analysis (ftsa). The rise of packages like robin and leidenbase highlights the growing importance of network analysis and community detection in various fields.


Efficiency and scalability are also key themes. Packages like sparsevctrs improve data handling, while fastml streamlines machine learning workflows. The increased popularity of prqlr suggests a move towards more efficient data manipulation through integration with other languages. Furthermore, the focus on improving the R development experience is evident with packages like box.lsp and box.linters, enhancing code quality and editor integration.


Finally, there's a notable emphasis on specialized data types and imputation techniques. Packages such as FuzzyImputationTest and rbiom cater to the needs of researchers working with fuzzy data and biological observation matrices, respectively. The rise of rhino indicates a growing demand for robust frameworks for building enterprise-level Shiny applications. This diverse range of packages reflects the expanding applications of R across various scientific disciplines.

Data provided by CRAN

Summary generated by Google Gemini Flash 1.5

Trending packages are the ones that were downloaded at least 1000 times during last week, and that substantially increased their download counts, compared to the average weekly downloads in the previous 24 weeks.

Data provided by CRAN