For this project, I leaned heavily on the sample solution after putting my original code out there. As one would expect for a fairly new data scientist, the minutiae has given me a hard time when it comes to graphing. Getting a graph is hard but knowing how to create the best graph for what you’re trying to express is really what will put me over the top. Once I get better with sizing, spacing, and understanding the quirks of how to brush up a visualization I’ll feel much better about my skillset.
Some conclusions from the data itself:
- Zimbabwe started the century in a bit of a bind, but they seem to be improving rapidly on both a GDP and life expectancy scale
- GDP and life expectancy are fairly related, as more GDP means more resources for medicinal improvements and safety nets
- Germany seems to be stagnating both economically and from a life expectancy standpoint
- Mexico has had some ups and down, but generally they improve over time
- China’s growth rate should alarm the U.S. as the world superpower, as China is catching up quick