| imbox | 0.9.8 | Python IMAP for Human beings | Mar 25, 2025 | MIT |
| madgrad | 1.2 | A general purpose PyTorch Optimizer | Mar 25, 2025 | MIT |
| panflute | 2.3.0 | Pythonic Pandoc filters | Mar 25, 2025 | BSD-3-Clause |
| polars | 0.13.31 | Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow(2) as memory model. | Mar 25, 2025 | MIT |
| pyactiveresource | 2.2.2 | ActiveResource for Python | Mar 25, 2025 | MIT |
| pydeps | 1.10.12 | Display module dependencies | Mar 25, 2025 | BSD-2-Clause |
| pymedio | 0.2.8 | read arbitrary medical images in python | Mar 25, 2025 | Apache-2.0 |
| r-btw | 1.1.0 | A Toolkit for Connecting R and Large Language Models | Jan 6, 2026 | MIT |
| r-clusterr | 1.3.3 | Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids
and Affinity Propagation Clustering | Mar 25, 2025 | GPL-3.0-only |
| r-comorbidity | 1.1.0 | Computing Comorbidity Scores | Apr 10, 2026 | GPL-3.0-or-later |
| r-dalextra | 2.3.0 | Provides wrapper of various machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the interpretable machine learning, there are more and more new ideas for explaining black-box models, that are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek (2018) <arXiv:1806.08915> explainer for many type of models including those created using 'python' 'scikit-learn' and 'keras' libraries, and 'java' 'h2o' library. Important part of the package is Champion-Challenger analysis and innovative approach to model performance across subsets of test data presented in Funnel Plot. | Mar 25, 2025 | GPL-3 |
| r-docxtractr | 0.6.5 | 'Microsoft Word' 'docx' files provide an 'XML' structure that is fairly straightforward to navigate, especially when it applies to 'Word' tables and comments. Tools are provided to determine table count/structure, comment count and also to extract/clean tables and comments from 'Microsoft Word' 'docx' documents. There is also nascent support for '.doc' and '.pptx' files. | Mar 25, 2025 | MIT |
| r-epitools | 0.5_10.1 | Tools for training and practicing epidemiologists including methods for two-way and multi-way contingency tables. | Mar 25, 2025 | GPL-2 |
| r-esc | 0.5.1 | Implementation of the web-based 'Practical Meta-Analysis Effect Size Calculator' from David B. Wilson (<http://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator-Home.php>) in R. Based on the input, the effect size can be returned as standardized mean difference, Cohen's f, Hedges' g, Pearson's r or Fisher's transformation z, odds ratio or log odds, or eta squared effect size. | Mar 25, 2025 | GPL-3 |
| r-finalfit | 1.0.3 | Generate regression results tables and plots in final format for publication. Explore models and export directly to PDF and 'Word' using 'RMarkdown'. | Mar 25, 2025 | MIT |
| r-fontawesome | 0.2.2 | Easily and flexibly insert 'Font Awesome' icons into 'R Markdown' documents and 'Shiny' apps. These icons can be inserted into HTML content through inline 'SVG' tags or 'i' tags. There is also a utility function for exporting 'Font Awesome' icons as 'PNG' images for those situations where raster graphics are needed. | Mar 25, 2025 | MIT |
| r-forestploter | 1.1.3 | Create a Flexible Forest Plot | Mar 27, 2026 | MIT |
| r-ftextra | 0.4.0 | Build display tables easily by extending the functionality of the 'flextable' package. Features include spanning header, grouping rows, parsing markdown and so on. | Mar 25, 2025 | MIT |
| r-gamlss.add | 5.1 | Interface for extra smooth functions including tensor products, neural networks and decision trees. | Mar 25, 2025 | LGPLLR |
| r-gamlss.dist | 6.1_1 | A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' or a 'logit' transformation respectively. | Mar 25, 2025 | ZPL-2.0 |
| r-gamlss.foreach | 1.1_6 | Computational intensive calculations for Generalized Additive Models for Location Scale and Shape, <doi:10.1111/j.1467-9876.2005.00510.x>. | Mar 25, 2025 | ZPL-2.0 |
| r-gamlss.ggplots | 2.1_12 | Functions for plotting Generalized Additive Models for Location Scale and Shape from the 'gamlss' package, Stasinopoulos and Rigby (2007) <doi:10.18637/jss.v023.i07>, using the graphical methods from 'ggplot2'. | Mar 25, 2025 | ZPL-2.0 |
| r-gamlss.inf | 1.0_1 | This is an add-on package to 'gamlss'. The purpose of this package is to allow users to fit GAMLSS (Generalised Additive Models for Location Scale and Shape) models when the response variable is defined either in the intervals [0,1), (0,1] and [0,1] (inflated at zero and/or one distributions), or in the positive real line including zero (zero-adjusted distributions). The mass points at zero and/or one are treated as extra parameters with the possibility to include a linear predictor for both. The package also allows transformed or truncated distributions from the GAMLSS family to be used for the continuous part of the distribution. Standard methods and GAMLSS diagnostics can be used with the resulting fitted object. | Mar 25, 2025 | ZPL-2.0 |
| r-ganttrify | 0.0.0.9007 | 'ganttrify' facilitates the creation of nice-looking Gantt charts, commonly used in project proposals and project management. | Mar 25, 2025 | GPL-3 |
| r-genpwr | 1.0.4 | Power and sample size calculations for genetic association studies allowing for misspecification of the model of genetic susceptibility. "Hum Hered. 2019;84(6):256-271.<doi:10.1159/000508558>. Epub 2020 Jul 28." Power and/or sample size can be calculated for logistic (case/control study design) and linear (continuous phenotype) regression models, using additive, dominant, recessive or degree of freedom coding of the genetic covariate while assuming a true dominant, recessive or additive genetic effect. In addition, power and sample size calculations can be performed for gene by environment interactions. These methods are extensions of Gauderman (2002) <doi:10.1093/aje/155.5.478> and Gauderman (2002) <doi:10.1002/sim.973> and are described in: Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification. American Society of Human Genetics. October 2018, San Diego. | Mar 25, 2025 | GPL-3 |
