Yousef Tarek Nathan — AI & Data Science Developer

Data Analysis

World Happiness Data Analysis & Dashboard

Interactive data analysis and visualization dashboard exploring global happiness trends and their relationship with key socio-economic indicators from 2015–2019.

TECHNOLOGIES

Python · Pandas · NumPy · Matplotlib · Plotly · Plotly Dash

Charts and analytics dashboard on a laptop

PROBLEM

Analyze global happiness data to identify trends and relationships between happiness scores and key socio-economic factors.

APPROACH

Cleaned and integrated multi-year datasets, performed exploratory data analysis, analyzed correlations and trends, and developed an interactive Plotly Dash dashboard with dynamic filtering.

DATASET

World Happiness Report dataset covering 2015–2019, including happiness scores and indicators such as GDP, social support, life expectancy, freedom, generosity, and corruption.

IMPLEMENTATION

Data preprocessing with Pandas and NumPy, exploratory analysis and statistical visualization with Matplotlib and Plotly, followed by interactive dashboard development using Plotly Dash.

RESULTS

Built 13+ interactive visualizations for comparing happiness trends, distributions, relationships, and socio-economic indicators.

KEY INSIGHTS

Revealed relationships between happiness scores and socio-economic indicators, enabling users to compare countries, explore trends over time, identify distributions and outliers, and investigate factor relationships interactively.

Yousef Tarek Nathan

AI & Data Science Developer