Tidy Flowchart Generator

Creates participant flow diagrams directly from a dataframe. Representing the flow of participants through each stage of a study, especially in clinical trials, is essential to assess the generalisability and validity of the results. This package provides a set of functions that can be combined with a pipe operator to create all kinds of flowcharts from a data frame in an easy way.

Tidy Finance Helper Functions

Helper functions for empirical research in financial economics, addressing a variety of topics covered in Scheuch, Voigt, and Weiss (2023) . The package is designed to provide shortcuts for issues extensively discussed in the book, facilitating easier application of its concepts. For more information and resources related to the book, visit < https://www.tidy-finance.org/r/index.html>.

Working with Sets the Tidy Way

Implements a class and methods to work with sets, doing intersection, union, complementary sets, power sets, cartesian product and other set operations in a "tidy" way. These set operations are available for both classical sets and fuzzy sets. Import sets from several formats or from other several data structures.

Tidy Standardized Mean Differences

Tidy standardized mean differences ('SMDs'). 'tidysmd' uses the 'smd' package to calculate standardized mean differences for variables in a data frame, returning the results in a tidy format.

Tidy Bayesian Vector Autoregression

Functions to prepare tidy objects from estimated models via 'BVAR' (see Kuschnig & Vashold, 2019 ) and visualisation thereof. Bridges the gap between estimating models with 'BVAR' and plotting the results in a more sophisticated way with 'ggplot2' as well as passing them on in a tidy format.

A Tidy Solution for Epidemiological Data

Offers a tidy solution for epidemiological data. It houses a range of functions for epidemiologists and public health data wizards for data management and cleaning.

Tidying Methods for Mixed Models

Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.

A Tidy Wrapper Around 'gtrendsR'

Access Google Trends information. This package provides a tidy wrapper to the 'gtrendsR' package. Use four spaces when indenting paragraphs within the Description.

Tidy Data Validation Reports

Tools for creating data validation pipelines and tidy reports. This package offers a framework for exploring and validating data frame like objects using 'dplyr' grammar of data manipulation.

Heatmaps from Tidy Data

The goal of 'tidyheatmaps' is to simplify the generation of publication-ready heatmaps from tidy data. By offering an interface to the powerful 'pheatmap' package, it allows for the effortless creation of intricate heatmaps with minimal code.