OECD Well-being Indicators Data App

Inspiration

The motivation behind this project stemmed from a desire to understand what truly defines quality of life across nations. The OECD Well-Being dataset captures diverse dimensions such as health, education, income, environment, and work-life balance. I wanted to build an interactive analytics app that transforms this complex data into intuitive, visual insights — empowering users to explore and compare well-being across countries.

Objective

To design a data-driven analytics dashboard that enables users to:

Compare global well-being indicators interactively.

Identify trends and correlations among economic, social, and environmental factors.

Support data-backed discussions on sustainable and inclusive development.

Approach & Tools

Data Source: OECD Better Life Index dataset.

Tech Stack: Python, Plotly Dash, Pandas, and Plotly Express.

Process:

Cleaned and normalized country-level well-being data.

Computed derived metrics such as a “Composite Well-Being Score.”

Designed interactive visualizations — radar, scatter, and bar charts — for multidimensional analysis.

Key Features

Country and indicator-based filtering for custom comparisons.

Interactive visualization of 11 well-being dimensions.

Hover-enabled tooltips and clean UI for a seamless user experience.

Correlation insights between income, life satisfaction, and other well-being factors.

Insights

Scandinavian countries consistently lead in well-being, driven by balance across social and environmental dimensions.

Higher income doesn’t always translate into higher life satisfaction — social support and work-life balance matter equally.

Emerging economies show encouraging improvements in education and health metrics.

Challenges & Learnings

The main challenges were managing missing data and designing a user-friendly yet responsive layout. This project enhanced my skills in data storytelling, interactive dashboarding, and user-centric design — showing how open data and analytics can bridge the gap between numbers and human impact.

Built With

• plotly
• plotly-cloud
• plotly-studio