Download and Tidy Data from the 'OECD'

Provides clean, tidy access to key economic indicators published by the 'Organisation for Economic Co-operation and Development' ('OECD'), covering GDP, CPI inflation, unemployment, tax revenue, government deficit, health expenditure, education expenditure, income inequality, labour productivity, and current account balance across all 38 'OECD' member countries. Data is downloaded from the 'OECD Data Explorer' API < https://data-explorer.oecd.org> on first use and cached locally for subsequent calls. Returns tidy long-format data frames ready for analysis and visualisation.

Simple Scraping and Tidy Webpage Summaries

Simple tools for scraping webpages, extracting common html tags and parsing contents to a tidy, tabular format. Tools help with extraction of page titles, links, images, rss feeds, social media handles and page metadata.

Download and Tidy IPC and CH Data

Utilities to access Integrated Food Security Phase Classification (IPC) and Cadre Harmonisé (CH) food security data. Wrapper functions are available for all of the 'IPC-CH' Public API (< https://docs.api.ipcinfo.org>) simplified and advanced endpoints to easily download the data in a clean and tidy format.

A Tidy Framework for Changepoint Detection Analysis

Changepoint detection algorithms for R are widespread but have different interfaces and reporting conventions. This makes the comparative analysis of results difficult. We solve this problem by providing a tidy, unified interface for several different changepoint detection algorithms. We also provide consistent numerical and graphical reporting leveraging the 'broom' and 'ggplot2' packages.

Tidy Common R Statistical Functions

Provides functions to scale, log-transform and fit linear models within a 'tidyverse'-style R code framework. Intended to smooth over inconsistencies in output of base R statistical functions, allowing ease of teaching, learning and daily use. Inspired by the tidy principles used in 'broom' Robinson (2017) .

A Tidy Implementation of the Synthetic Control Method

A synthetic control offers a way of evaluating the effect of an intervention in comparative case studies. The package makes a number of improvements when implementing the method in R. These improvements allow users to inspect, visualize, and tune the synthetic control more easily. A key benefit of a tidy implementation is that the entire preparation process for building the synthetic control can be accomplished in a single pipe.

Simple Conjoint Tidying, Analysis, and Visualization

Simple tidying, analysis, and visualization of conjoint (factorial) experiments, including estimation and visualization of average marginal component effects ('AMCEs') and marginal means ('MMs') for weighted and un-weighted survey data, along with useful reference category diagnostics and statistical tests. Estimation of 'AMCEs' is based upon methods described by Hainmueller, Hopkins, and Yamamoto (2014) .

A Tidy Interface to the 'Valhalla' Routing Engine

An interface to the 'Valhalla' routing engine’s application programming interfaces (APIs) for turn-by-turn routing, isochrones, and origin-destination analyses. Also includes several user-friendly functions for plotting outputs, and strives to follow "tidy" design principles. Please note that this package requires access to a running instance of 'Valhalla', which is open source and can be downloaded from < https://github.com/valhalla/valhalla>.

Tidy Estimation of Heterogeneous Treatment Effects

Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (2023) . You provide a simple recipe for what machine learning algorithms to use in estimating the nuisance functions and 'tidyhte' will take care of cross-validation, estimation, model selection, diagnostics and construction of relevant quantities of interest about the variability of treatment effects.

Access Tidy Education Finance Data

Provides easy access to tidy education finance data using Bellwether's methodology to combine NCES F-33 Survey, Census Bureau Small Area Income Poverty Estimates (SAIPE), and community data from the ACS 5-Year Estimates. The package simplifies downloading, caching, and filtering education finance data by year and state, enabling researchers and analysts to explore K-12 education funding patterns, revenue sources, expenditure categories, and demographic factors across U.S. school districts.