wdiexplorer: An R package Designed for Exploratory Analysis of World Development Indicators (WDI) Data

TL;DR

The paper introduces the wdiexplorer R package, which facilitates exploratory analysis, visualization, and diagnostics of World Development Indicators data for identifying patterns and outliers in global development metrics.

Contribution

The paper presents a new R package, wdiexplorer, that streamlines the analysis and visualization of WDI data, enhancing exploratory capabilities for researchers.

Findings

Demonstrated the package's functionalities with PM2.5 air pollution data.

Identified patterns and outliers across countries and groups.

Showcased efficient exploration of WDI datasets.

Abstract

The World Development Indicators (WDI) database provides a wide range of global development data, maintained and published by the World Bank. Our \textit{wdiexplorer} package offers a comprehensive workflow that sources WDI data via the \textit{WDI} R package, prepares and explores country-level panel data of the WDI through computational functions to calculate diagnostic metrics and visualise the outputs. By leveraging the functionalities of \textit{wdiexplorer} package, users can efficiently explore any indicator dataset of the WDI, compute diagnostic indices, and visualise the metrics by incorporating the pre-defined grouping structures to identify patterns, outliers, and other interesting features of temporal behaviours. This paper presents the \textit{wdiexplorer} package, demonstrates its functionalities using the WDI: PM$_{2.5}$ air pollution dataset, and discusses the observed patterns and outliers across countries and within groups of country-level panel data.