Analysis of unicef

Data preparation

We are reading unicef_indicator_1.csv,unicef_indicator_2.csv & unicef_metadata.csv into R environment for analysis. We have generate a unique key based on country code and year to join unicef_indicator_1.csv with unicef_metadata.csv. This helps us to get some trends by combining both files

In below world map we have highlighted countries with high Percentage Children suffering exactly three deprivation. These countries require more efforts from WHO team. Most of the countries lies in Africa (which is a low per captia country and do not have stable goverments)

Correlation Between Per captia income and Life expectancy

There is a high positive correlation of .61 which means that countries with high per captia income tends to have greater life expectancy.

Trend between Military Expenditure over Years

Top Deprived Countries

Out of 10 deprived countries 9 are in Africa and 1 in asia. This means indicators in Africa are quite poor and more efforts are needed in Africa.

Top Deprived Countries Bar chart

For top deprived countries it is observed that Male are more prone to deficiencies than female. Created a bar chart depicting the same.