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cff-version: 1.2.0
message: 'To cite package "wdiexplorer" in publications use:'
type: software
license: MIT
title: 'wdiexplorer: Explore World Development Indicators Data'
version: 0.1.1
doi: 10.32614/CRAN.package.wdiexplorer
abstract: 'Provides a workflow for exploring World Development Indicators (WDI) country-level
  panel data. It downloads WDI data using the ''WDI'' package and computes diagnostic
  indices that capture the temporal behaviour of the data by incorporating the grouping
  structure of the data. The set of diagnostic indices implemented includes variation
  features, trend and shape features, and sequential temporal features. This method
  is described in Akinfenwa, Cahill, and Hurley (2025) "wdiexplorer: An R package
  Designed for Exploratory Analysis of World Development Indicators (WDI) Data" <https://doi.org/10.48550/arXiv.2511.07027>.
  We adapt the clustering diagnostics and visualisation methodology described in Rousseeuw
  (1987) <https://doi.org/10.1016/0377-0427(87)90125-7> and selected time series features
  from Hyndman and Athanasopoulos (2021) "Forecasting: Principles and Practice" <https://otexts.com/fpp3/>.'
authors:
- family-names: Akinfenwa
  given-names: Oluwayomi
  email: oluwayomiakinfenwa@gmail.com
- family-names: Cahill
  given-names: Niamh
  email: niamh.cahill@mu.ie
- family-names: Hurley
  given-names: Catherine
  email: catherine.hurley@mu.ie
repository: https://oluwayomi-olaitan.r-universe.dev
repository-code: https://github.com/Oluwayomi-Olaitan/wdiexplorer
commit: 2ae1e646704d9980039360e030a3e3bb03d61895
url: https://github.com/Oluwayomi-Olaitan/wdiexplorer
date-released: '2026-04-20'
contact:
- family-names: Akinfenwa
  given-names: Oluwayomi
  email: oluwayomiakinfenwa@gmail.com