Humanitarian Aid Project
Charitable groups work tirelessly to combat poverty and assist those struggling, particularly those in marginalized communities, by supplying them with essential resources and aid during times of crisis and natural disasters.
This project aims to aggregate and organize data to identify which Asian countries require the most financial assistance from humanitarian groups. You will use various tools and techniques to organize and clean the data, including the pandas and NumPy libraries. The final product will be a dataset in the form of a CSV file that can be used for further analysis.
You will be using two datasets we have generated for this project's specific purpose. These datasets contain information on various countries in Asia. It's crucial to remember that the datasets should only be used within the context of this project for research and analysis and not for making any conclusions or predictions outside the project. These datasets combined contain the following columns with social and economic data.
country: Name of the country.
child_mort: Death of children under five years of age per 1,000 live births.
health: Total health spending as a percentage of 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 child would live if the current mortality patterns remained the same.
total_fer: The number of children that would be born to each person if the current age-fertility rates remain the same.
exports: Exports of goods and services. Given as a percentage of the total GDP.
imports: Imports of goods and services. Given as a percentage of the total GDP.
gdpp: The GDP per capita. Calculated as the total GDP divided by the total population.