Welcome to the International Happiness Report Analysis :)
- Policy-relevant data analysis using Python and interactive Streamlit dashboards
- Insights into factors driving happiness across countries
- Clear, reproducible workflow with interactive visualizations for stakeholders
Discover What Makes People Happy across nations through an interactive Streamlit dashboard. In this analysis, the dataset we used is based on International world reports for the period between 2005 et 2021.
The most interesting takeoffs from our analysis show the following:
- Correlation between 'Log GDP per capita', 'Social support', 'Freedom to make life choices', and 'Generosity' coefficients, and happiness.
- Policymakers can use these insights to focus on improving economic conditions, social support systems, and freedom for individuals, which are crucial factors contributing to happiness in societies.
- Further analysis and policy interventions can aim to enhance these factors to promote overall well-being and happiness across different countries.
- Policy-relevant data analysis using Python and interactive Streamlit dashboards
- Insights into factors driving happiness across countries
- Clear, reproducible workflow with interactive visualizations for stakeholders
pandas matplotlib streamlit
Clone the repository
git clone https://github.com/Amirabs7/HappinessReport.git cd HappinessReport
pip install -r requirements.txt
streamlit run app.py