Datasets:

sleepysaurus
/

DataVerse

---
license: mit
task_categories:
  - tabular-classification
  - tabular-regression
language:
  - en
tags:
  - economics
  - development
  - world-bank
  - global
  - climate
  - healthcare
  - dataverse-2026
pretty_name: DataVerse — Global Development Indicators Dataset
size_categories:
  - 1K<n<10K
---

# 🌐 DataVerse — Global Development Indicators Dataset

This dataset was compiled for **DataVerse-2026**, a data analytics competition organized by the Departmental Statistics Association (DSA), Department of Statistics, Faculty of Science, **The Maharaja Sayajirao University of Baroda**. The competition challenges participants to solve real-world problems through visualization, machine learning, and analytical storytelling.

> 📅 Competition Dates: Feb 26–28, 2026 · 📍 Venue: Dept. of Statistics, MSU Baroda · 👥 Team Size: 1–4 Members

---

## 📋 Dataset Overview

A longitudinal panel dataset covering **global development indicators** across world regions and country groups from **2000 to 2020**. Each row represents a region-year observation and spans economic, environmental, health, digital, and governance dimensions.

The dataset is structured around aggregated World Bank-style regional groupings (e.g., Africa Eastern and Southern, Arab World, Central Europe and the Baltics, etc.) rather than individual countries, making it well-suited for comparative regional analysis.

---

## 📊 Features

The dataset contains **47 columns** organized into the following thematic groups:

### 🆔 Identifiers
| Column | Description |
|---|---|
| `year` | Year of observation (2000–2020) |
| `country_code` | World Bank region/group code (e.g., `AFE`, `ARB`, `CEB`) |
| `country_name` | Full name of the region or country group |
| `region` | Sub-region classification *(often null for aggregated groups)* |
| `income_group` | World Bank income classification *(often null)* |
| `currency_unit` | Primary currency *(often null for regional aggregates)* |

### 💰 Economic Indicators
| Column | Description |
|---|---|
| `gdp_usd` | GDP in current USD |
| `population` | Total population |
| `gdp_per_capita` | GDP per capita (USD) |
| `inflation_rate` | Annual inflation rate (%) |
| `unemployment_rate` | Unemployment rate (%) |
| `fdi_pct_gdp` | Foreign direct investment as % of GDP |

### 🌱 Environmental Indicators
| Column | Description |
|---|---|
| `co2_emissions_kt` | CO₂ emissions in kilotons |
| `energy_use_per_capita` | Energy use per capita (kg oil equivalent) |
| `renewable_energy_pct` | Renewable energy as % of total |
| `forest_area_pct` | Forest area as % of land area |

### ❤️ Health & Social Indicators
| Column | Description |
|---|---|
| `life_expectancy` | Average life expectancy at birth |
| `child_mortality` | Under-5 mortality rate (per 1,000 live births) |
| `health_expenditure_pct_gdp` | Health expenditure as % of GDP |
| `hospital_beds_per_1000` | Hospital beds per 1,000 people |
| `physicians_per_1000` | Physicians per 1,000 people |
| `electricity_access_pct` | Population with access to electricity (%) |
| `school_enrollment_secondary` | Secondary school enrollment rate |

### 📡 Digital & Connectivity Indicators
| Column | Description |
|---|---|
| `internet_usage_pct` | Internet users as % of population |
| `mobile_subscriptions_per_100` | Mobile subscriptions per 100 people |

### 📐 Derived / Composite Indices
| Column | Description |
|---|---|
| `calculated_gdp_per_capita` | Recalculated GDP per capita |
| `real_economic_growth_indicator` | Derived economic growth metric |
| `econ_opportunity_index` | Composite economic opportunity score |
| `co2_emissions_per_capita_tons` | Per capita CO₂ emissions (metric tons) |
| `co2_intensity_per_million_gdp` | CO₂ intensity per million USD of GDP |
| `green_transition_score` | Score reflecting transition to green energy |
| `ecological_preservation_index` | Index measuring ecological health |
| `renewable_energy_efficiency` | Efficiency ratio of renewable energy use |
| `human_development_composite` | Composite HDI-style score |
| `healthcare_capacity_index` | Derived healthcare system capacity score |
| `digital_connectivity_index` | Composite digital access/readiness score |
| `health_development_ratio` | Ratio of health indicators to development level |
| `education_health_ratio` | Ratio of education to health indicators |
| `human_development_index` | HDI estimate |
| `climate_vulnerability_index` | Climate risk and vulnerability score |
| `digital_readiness_score` | Digital readiness composite |
| `governance_quality_index` | Governance quality composite |
| `global_resilience_score` | Overall resilience composite |
| `global_development_resilience_index` | Master composite development index |

### 🗓️ Temporal Features
| Column | Description |
|---|---|
| `years_since_2000` | Years elapsed since 2000 |
| `years_since_century` | Same as above (century baseline) |
| `is_pandemic_period` | Binary flag — `1` for year 2020 (COVID-19) |

---

## 🔍 Potential Use Cases

This dataset is particularly well-suited for:

- **Exploratory Data Analysis (EDA)** — regional trends, missing data patterns, distributions
- **Time-series forecasting** — predict GDP, HDI, or emissions over time
- **Clustering / Unsupervised learning** — group regions by development profile
- **Regression modeling** — predict composite indices from base indicators
- **Dashboard / Visualization** — build interactive development dashboards
- **Analytical storytelling** — narrate global development trends

---

## ⚠️ Data Notes

- Many columns contain `null` values, especially for later years (2016–2020) where source data was unavailable.
- The dataset uses **regional aggregates** (World Bank group codes), not individual country data.
- The `is_pandemic_period` flag marks 2020 as a notable anomaly year — many indicators show sharp discontinuities.
- Some derived indices may have been computed by the dataset author and are not direct World Bank outputs.

---

## 🏆 About DataVerse-2026

DataVerse-2026 is a data analytics hackathon organized by the **Departmental Statistics Association (DSA)**, Department of Statistics, Faculty of Science, MSU Baroda (Est. 1949). The competition runs over 2 rounds and spans 3 domains, bringing together students to demonstrate data-driven thinking, creativity, and collaboration.

- 🌐 Website: [threed2y.github.io/DataVerse-2026](https://threed2y.github.io/DataVerse-2026)
- 📧 Contact: [dataversestats@gmail.com](mailto:dataversestats@gmail.com)
- 🏛️ Organizer:Departmental Statistics Association, Dept. of Statistics, Faculty of Science, The Maharaja Sayajirao University of Baroda

---

## 📄 License

This dataset is released under the **MIT License**.