World Happiness Report Data Analysis

This project analyzes the World Happiness Report data from 2015 to 2019. The data includes information on the happiness score, six contributing factors to happiness, and other socio-economic indicators for over 150 countries.

The project uses Python to clean, analyze, and visualize the data. The following are some of the key findings of the project:

• The top 10 happiest countries in the world are Finland, Denmark, Norway, Iceland, Netherlands, Switzerland, Sweden, New Zealand, Austria, and Canada.
• The six factors that contribute most to happiness are:
  • GDP per capita
  • Social support
  • Healthy life expectancy
  • Freedom to make life choices
  • Generosity
  • Perception of corruption
• The happiness score of a country has changed significantly between 2015 and 2019. Some countries have experienced a significant increase in happiness, while others have experienced a significant decrease.
• There is a positive correlation between the happiness score of a country and the six contributing factors to happiness.

To run the project

1. Install the required Python packages.

pip install pandas pip install matplotlib pip install seaborn

2. Clone the repository.
3. Run the main.ipynb file.

To contribute to the project

1. Fork the repository.
2. Make your changes.
3. Submit a pull request.

License

The project is licensed under the MIT License.

Annotation

This project is prepared for Data Science Projects by PatikaDev.