A Streamlit-based web application that visualizes the relationship between GDP, Happiness Score, and Generosity across various countries.
This project presents an interactive dashboard allowing users to explore how economic and social factors correlate with happiness indicators. Users can dynamically select variables to analyze and gain insights through visualizations.
- Interactive selection of X and Y axes for plotting
- Dynamic scatter plots with hover tooltips
- Clean and responsive UI using Streamlit
- Data sourced from a CSV file containing global happiness metrics
- Python
- Streamlit
- Plotly
- Pandas
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Clone the repository: git clone https://github.com/DziwiszBB/Data-Visualization-App.git cd in-search-for-happiness
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Install the required packages: pip install -r requirements.txt
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Run the application: streamlit run main.py
The dataset 004 happy.csv includes metrics such as GDP per capita, Happiness Score, and Generosity for various countries.
File 004 happy.csv contains the following columns:
Country: Name of the country.GDP per capita: Gross Domestic Product per capita, reflecting the economic output per person.Happiness Score: A measure of the average happiness level of the country's population, typically on a scale from 0 to 10.Generosity: A metric indicating the generosity of the population, often based on charitable donations and helping behavior.
Sample data row:
| Country | GDP per capita | Happiness Score | Generosity |
|---|---|---|---|
| Norway | 1.616 | 7.537 | 0.362 |
This project is licensed under the MIT License. See the LICENSE file for details.
Piotr Dziwisz