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
📧 Contact: 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.