1 Child Mortality
In this first part of Task 2, you should write a Python script that reads and analyses the child mortality data file (WHOSIS_MDG_000003.csv) and produce at least FIVE useful graphs that give insight into the data trends.
You should produce the following graphs:
1. graph theunder-five mortality rates of all countries in 1990, sorted from lowest rate to highest rate. (If the graph is too crowded, you can show just each 10th country, or show the first 10 and last 10 countries).
2. graph the under-five mortality rates as above, but for 2015.
3. choose three representative countries in different areas of the world, then create a line graph showing the trends in under-five mortality in those countries over the years from 1990 to 2015.
4. for those same three countries, graph the reduction in under-five mortality rates over the 1990/2015 period - that is, the 1990 rate divided by the 2015 rate.
5. an under-five mortality graph of your choice... (explain why you chose that graph, and what conclusions you draw from the graph).
2 Child Mortality and Country Types
In this second part of Task 2, you should write another Python script that reads and analyses the country metadata (COUNTRY.json) and merges it with the child mortality data from Part 1, to allow you to do some higher-level analysis of under-fivemortality trends.
Your report should include at least twographs that display or compare under-five mortality in different regions of the world (using the 'WHO_REGION' string to group the countries).
You report should include at least two graphs that compare under-five mortality across different income groupings (using the 'WORLD_BANK_INCOME_GROUP' string to classify the countries).
Attachment:- Child-Mortality.rar