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Tidy Plots for Scientific Papers
The goal of 'tidyplots' is to streamline the creation of publication-ready plots for scientific papers. It allows to gradually add, remove and adjust plot components using a consistent and intuitive syntax.
Tidy Verbs for Fast Data Manipulation
A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.
Tidy Dataframes and Expressions with Statistical Details
Utilities for producing dataframes with rich details for the
most common types of statistical approaches and tests: parametric,
nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation
analyses, contingency table analyses, and meta-analyses. The functions
are pipe-friendly and provide a consistent syntax to work with tidy
data. These dataframes additionally contain expressions with
statistical details, and can be used in graphing packages. This
package also forms the statistical processing backend for
'ggstatsplot'. References: Patil (2021)
Tidy Integration of Large Language Models
A tidy interface for integrating large language model (LLM) APIs such as 'Claude', 'OpenAI', 'Gemini', 'Mistral', and local models via 'Ollama' into R workflows. The package supports text, image, audio, video, and document interactions; a unified media interface for attaching inline files or uploading to provider file stores; batch request APIs for cost-efficient large-scale processing; and a pipeline-oriented interface for seamless integration into data workflows. Web services are available at < https://www.anthropic.com>, < https://openai.com>, < https://aistudio.google.com/>, < https://mistral.ai/> and < https://ollama.com>.
Tidy, Type-Safe 'prediction()' Methods
A one-function package containing prediction(), a type-safe alternative to predict() that always returns a data frame. The summary() method provides a data frame with average predictions, possibly over counterfactual versions of the data (à la the margins command in 'Stata'). Marginal effect estimation is provided by the related package, 'margins' < https://cran.r-project.org/package=margins>. The package currently supports common model types (e.g., lm, glm) from the 'stats' package, as well as numerous other model classes from other add-on packages. See the README file or main package documentation page for a complete listing.
Easily Install and Load the 'Tidymodels' Packages
The tidy modeling "verse" is a collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
Tidy GeoRSS
In order to easily integrate geoRSS data into analysis, 'tidygeoRSS' parses 'geo' feeds and returns tidy simple features data frames.
Gene Orthologs for Model Organisms in a Tidy Data Format
Genomic analysis of model organisms frequently requires the
use of databases based on human data or making comparisons to
patient-derived resources. This requires harmonization of gene names
into the same gene space. The 'babelgene' R package converts between
human and non-human gene orthologs/homologs. The package integrates
orthology assertion predictions sourced from multiple databases as
compiled by the HGNC Comparison of Orthology Predictions (HCOP)
(Wright et al. 2005
Tidy Complex 'JSON'
Turn complex 'JSON' data into tidy data frames.
Tidy Tibbles of Noegletal
Work with data from < https://noegletal.dk> in a tidy manner. Tidy up previously downloaded data or retrieve new data directly from the comfort of R. You can also browse an up-to-date list of available data, including thorough variable descriptions.