🌪️ InspectAir is an advanced, user-friendly interactive dashboard designed to provide comprehensive insights into air quality across the globe. 🌬️ 🌍
-
Updated
May 30, 2024 - HTML
#
who-data
Here are 10 public repositories matching this topic...
A meta-mcp offering a window into the exciting world of open data sources
opendata sec-edgar rechtspraak eurostat-data overpass federal-register usgs-earthquake who-data copernicus-data-space mcp-servers meta-mcp cbs-data us-nasa
-
Updated
May 12, 2026 - Python
Predicts a country's WHO Universal Health Coverage level (Low/Medium/High) from workforce and infrastructure data. Decision Tree, Random Forest, and Gradient Boosting built from scratch in NumPy
data-science machine-learning random-forest healthcare decision-tree from-scratch gradient-boosting who-data
-
Updated
Apr 16, 2026 - Jupyter Notebook
End-to-end analysis of global PM2.5 air pollution and air-pollution-attributable mortality using WHO data, with interactive Power BI dashboards and Python-based EDA.
python data-science data-visualization public-health data-analysis air-pollution pm25 environmental-health who-data
-
Updated
Jan 20, 2026 - Jupyter Notebook
A modern, interactive web application that visualizes your life progress by calculating your age and comparing it to the expected life expectancy based on your gender and location. Built with React, Vite, and Tailwind CSS.
data-visualization web-application statistical-analysis react-app responsive-design age-calculator dark-mode progress-tracker modern-ui life-expectancy tailwindcss vite theme-toggle who-data interactive-dashboard life-progress health-metrics health-stats demographic-data life-journey
-
Updated
Jul 30, 2025 - JavaScript
SQL-based disease outbreak monitoring system using WHO data
mysql dashboard power-bi data-visualization public-health data-analysis covid-19 who-data outbreak-monitoring
-
Updated
Apr 26, 2026
Predicting average life expectancy by country using WHO data
-
Updated
Apr 10, 2025 - Jupyter Notebook
🚗 World Road Safety Analysis - Power BI Report 📊
-
Updated
Apr 25, 2026 - SCSS
Analyzed 553K+ WHO COVID-19 records across 5 countries using Pandas & NumPy identified Omicron as the deadliest wave peaking January 2022.
-
Updated
Apr 19, 2026 - Jupyter Notebook
dashboard power-bi data-visualization public-health epidemiology dax health-data who-data healtcare-analytics
-
Updated
Feb 11, 2026
Improve this page
Add a description, image, and links to the who-data topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the who-data topic, visit your repo's landing page and select "manage topics."