Tidy Manipulation of Fourier Transformed Data

The 'fftab' package stores Fourier coefficients in a tibble and allows their manipulation in various ways. Functions are available for converting between complex, rectangular ('re', 'im'), and polar ('mod', 'arg') representations, as well as for extracting components as vectors or matrices. Inputs can include vectors, time series, and arrays of arbitrary dimensions, which are restored to their original form when inverting the transform. Since 'fftab' stores Fourier frequencies as columns in the tibble, many standard operations on spectral data can be easily performed using tidy packages like 'dplyr'.

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>.

Weighted Tidy Log Odds Ratio

How can we measure how the usage or frequency of some feature, such as words, differs across some group or set, such as documents? One option is to use the log odds ratio, but the log odds ratio alone does not account for sampling variability; we haven't counted every feature the same number of times so how do we know which differences are meaningful? Enter the weighted log odds, which 'tidylo' provides an implementation for, using tidy data principles. In particular, here we use the method outlined in Monroe, Colaresi, and Quinn (2008) to weight the log odds ratio by a prior. By default, the prior is estimated from the data itself, an empirical Bayes approach, but an uninformative prior is also available.

Download and Tidy 'HMRC' Statistical Data

Provides functions to download, parse, and tidy statistical data published by 'HM Revenue and Customs' ('HMRC') on 'GOV.UK'. Returns annotated 'hmrc_tbl' data frames with provenance metadata (source URL, fetch time, vintage, cell methods) for reproducible fiscal research. Covers monthly tax receipts (41 tax heads from 2008), 'VAT' (from 1973), fuel duties (from 1990), tobacco duties (from 1991), annual 'Corporation Tax' receipts, stamp duty, research and development tax credit statistics (from 2000), tax gap estimates, 'Income Tax' liabilities by income range, and monthly property transaction counts. File URLs are resolved at runtime via the 'GOV.UK' Content API < https://www.gov.uk/api/content>, so data is always current without hardcoded URLs. Files are cached locally between sessions.

Tidy and Streamlined Metabolomics Data Workflows

Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) , Stekhoven et al. (2012) , Tibshirani et al. (2017) , Troyanskaya et al. (2001) ), normalization (Bolstad et al. (2003) , Dieterle et al. (2006) , Zhao et al. (2020) ) transformation, centering and scaling (Van Den Berg et al. (2006) ) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) ) format for metabolomics data and is designed to make it easier to build elaborate analysis workflows and to integrate them with 'tidyverse' packages including 'dplyr' and 'ggplot2'.

A Service for Tidy Transcriptomics Software Suite

It provides generic methods that are used by more than one package, avoiding conflicts. This package will be imported by 'tidySingleCellExperiment' and 'tidyseurat'.

Tidy Schema Validation for Data Frames

Validate data.frames against schemas to ensure that data matches expectations. Define schemas using 'tidyselect' and predicate functions for type consistency, nullability, and more. Schema failure messages can be tailored for non-technical users and are ideal for user-facing applications such as in 'shiny' or 'plumber'.

Tidy Multiverse Analysis Made Simple

Extends 'multiverse' package (Sarma A., Kale A., Moon M., Taback N., Chevalier F., Hullman J., Kay M., 2021) , which allows users perform to create explorable multiverse analysis in R. This extension provides an additional level of abstraction to the 'multiverse' package with the aim of creating user friendly syntax to researchers, educators, and students in statistics. The 'mverse' syntax is designed to allow piping and takes hints from the 'tidyverse' grammar. The package allows users to define and inspect multiverse analysis using familiar syntax in R.

Generate Tidy Charts Inspired by 'IBCS'

There is a wide range of R packages created for data visualization, but still, there was no simple and easily accessible way to create clean and transparent charts - up to now. The 'tidycharts' package enables the user to generate charts compliant with International Business Communication Standards ('IBCS'). It means unified bar widths, colors, chart sizes, etc. Creating homogeneous reports has never been that easy! Additionally, users can apply semantic notation to indicate different data scenarios (plan, budget, forecast). What's more, it is possible to customize the charts by creating a personal color pallet with the possibility of switching to default options after the experiments. We wanted the package to be helpful in writing reports, so we also made joining charts in a one, clear image possible. All charts are generated in SVG format and can be shown in the 'RStudio' viewer pane or exported to HTML output of 'knitr'/'markdown'.