HELP International have been able to raise around $ 10 million. Now the CEO of the NGO needs to decide how to use this money strategically and effectively. So, CEO has to make decision to choose the countries that are in the direst need of aid. Hence, My job as a Data analyst is to categorise the countries using some socio-economic and health factors that determine the overall development of the country. Then I need to suggest the countries which the CEO needs to focus on the most.
HELP International is an international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities.
The project aims to use clustering techniques to categorize countries based on socio-economic and health factors, helping the CEO of an NGO determine which countries are in the greatest need of aid out of a $10 million budget. The analysis also involves assessing the clusters and grouping the countries into developed, developing, and undeveloped categories.
- country: Name of the country
- child_mort: Death of children under 5 years of age per 1000 live births
- exports: Exports of goods and services. Given as %age of the Total GDP
- health: Total health spending as %age of Total GDP
- imports: Imports of goods and services. Given as %age of the Total GDP
- Income: Net income per person
- Inflation: The measurement of the annual growth rate of the Total GDP
- life_expec: The average number of years a new born child would live if the current mortality patterns are to remain the same
- total_fer: The number of children that would be born to each woman if the current age-fertility rates remain the same.
- gdpp: The GDP per capita. Calculated as the Total GDP divided by the total population.