Tidy Messy Data

Tools to help to create tidy data, where each column is a variable, each row is an observation, and each cell contains a single value. 'tidyr' contains tools for changing the shape (pivoting) and hierarchy (nesting and 'unnesting') of a dataset, turning deeply nested lists into rectangular data frames ('rectangling'), and extracting values out of string columns. It also includes tools for working with missing values (both implicit and explicit).

Convert Statistical Objects into Tidy Tibbles

Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.

Functions for Base Types and Core R and 'Tidyverse' Features

A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.

A Tidy API for Graph Manipulation

A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.

Tidy Temporal Data Frames and Tools

Provides a 'tbl_ts' class (the 'tsibble') for temporal data in an data- and model-oriented format. The 'tsibble' provides tools to easily manipulate and analyse temporal data, such as filling in time gaps and aggregating over calendar periods.

Tidy Data and 'Geoms' for Bayesian Models

Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.

MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format

Provides the 'Molecular Signatures Database' (MSigDB) gene sets typically used with the 'Gene Set Enrichment Analysis' (GSEA) software (Subramanian et al. 2005 , Liberzon et al. 2015 ) in a standard R data frame with key-value pairs. The package includes the human genes as listed in MSigDB as well as the corresponding symbols and IDs for frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

Tidy Complex 'JSON'

Turn complex 'JSON' data into tidy data frames.

Tidy Interface to 'data.table'

A tidy interface to 'data.table', giving users the speed of 'data.table' while using tidyverse-like syntax.

Smooth and Tidy Spatial Features

Tools for smoothing and tidying spatial features (i.e. lines and polygons) to make them more aesthetically pleasing. Smooth curves, fill holes, and remove small fragments from lines and polygons.