Country Data Clustering

Brief Description of the Data

Countries in the world can be categorized according to their needs and their possessions. Some countries might have a huge amount of natural resources which helps them to increase their welfare level. Others may suffer from social and economic difficulties which prevent the community from accessing basic needs such as high-quality education, advanced healthcare, safety environment, etc. Because of this reason, it is possible to convey this extra wealth produced by other countries to developing ones to increase their socio-economic opportunities.

HELP International which is founded as a type of non-governmental organization aims to help less developed countries by supplying their basic needs and provide financial support to tackle extreme poverty during hard times. The problem is that how HELP International could decide a country whether it needs a subvention or not according to looking at the countries' socio-economic parameters? This is the question that needs to be answered by analyzing the countries' data.

HELP International provides a dataset that includes 167 countries (rows) and 10 feature columns. 9 of these feature columns show the socio-economic parameters of the countries and one of them is the name of the countries. There is no target column in this dataset. Details of these feature columns can be made briefly as,

country: This column depicts the name of the country.
child_mort: This feature shows the ratio of death of a child younger than 5 years old occurring due to natural and unnatural causes to 1000 live births.
exports: It shows the rate of exports of goods and services per capita. It is given as the %age of the GDP per capita.
health: This column shows the government spending on health services per capita. It is measured as %age GDP per capita.
imports: This column's values depict the imports of goods and services per capita of a government. It is measured in the same way as exports.
income: This feature is an important parameter that shows net revenue for each person in the country.
inflation: It means increment of prices and decrement of purchasing power of money. It is measured by the ratio of the annual growth to the total GDP.
life_expec: This is another important measure for a country to be assumed as a developed country. This feature depicts the average number of years a newborn child would live by assuming the mortality rate stays the same.
total_fer: This parameter shows the newborn child for each woman by considering the rate of age-fertility stays the same.
gdpp: Gross Domestic Production (GDP) which is an essential measure for a country to be assumed as developed or underdeveloped measured by per capita. It shows the economic activity within the country for one year by considering the nation's goods and services.

Main Objective: The main objective of this analysis is to clustering the countries by using their socio-economic parameters to decide which countries should take HELP International's subvention. This requires clustering the countries into different groups and designating their group's parameters to decide whether to give that money to this group or not. By doing this, the organization could use this money effectively and strategically to improve the living condition of countries in need.

Initial plan for data exploration

This dataset has only one categorical column which is the "country" column shows the name of the countries in this dataset. Just for the data exploration purpose, a column that shows the continental information of each country is created to categorize them further. It will help to see the distributions of the countries according to their socio-economic levels across continents. This will provide some insights into the possible categorization of the countries.