For this week, I decided to work with this dataset regarding poverty statistics from 97 countries. Data types associated with this dataset include birth rates, death rates, infant mortality rates, life expectancies, and per capita GDP.
First glance at the data, once I sorted it by GDP, it becomes obvious that countries that have high GDP per capita do well in most datatypes such as dead rates, infant mortality rates, and life expectancies. However, I wanted to see the data visualization in order to confirm what I hypothesized while looking at raw data.
This chart, which is sorted by GDP, shows that the life expectancy for both males and females increases as the GDP increases. This clearly illustrates that those living in countries where the average income per person is higher tents to live longer. You can tell by the cluster of condensed lines, that it is more concentrated and severe for those living in countries with the lowest GDP where the lowest life expectancy is 38.1 years. Meanwhile, the highest life expectancy reaches 80 years. That is a huge discrepancy and horrifying to visually be able to see that some people are living less than half as long as others due to their income. Consequently, the death rate is also very high (25%) in countries with the lower GDP per capita compared to wealthier countries (9.5%). The yellow line, however, suggests that these low income countries are having more children as their birth rate is extremely high. To understand this, I created a variable chart comparing the infant mortality rate with the birth rate.
This shows that the countries with the highest birth rates are also the countries with the highest infant mortality rate. It becomes obvious that families in poor countries are having more children because they’re experiencing far more child deaths than wealthy countries.
After looking at this dataset, it becomes obvious that having more money literally means you get to live more than twice as long as those with little or no money. It also means that you are far less likely to experience the death of your newborn.
This chart visualizes the obvious; if a country has a higher death rate, it also has a lower life expectancy. As the the death rate decreases, the life expectancy increases. These visualizations are able to clearly show the power of money and its affect on life. It is harder to see this from the data itself, but these visualizations make it incredibly clear.
Nice work, Jay.
This is interesting to see, because as much as I know these trends intellectually, it is really quite striking when I see if as a visual. The discrepancies of life expectancy and infant mortality between countries with higher GDP compared to lower GDPS is astounding. It would be interesting to also see the ways that education and the human development index would factor in.