DATA150

9/30 essay: Go to the Gapminder data site (founded by Hans Rosling). The x and y axes can be changed with the little arrows. The year can be changed with the slider at the bottom. You can even have the plot play through time. Each bubble represents a nation and can be selected and deselected in the right panel. There’s a two minute “How to” video at the top as well. Pick at least one configuration (life expectancy vs income in the UK and Cuba over the past 80 years, for example). Try any combination(s) you like (no wrong answers here). Write what data you are displaying. Write about what you see or what surprises you, if anything. As best you can, connect what you see to ideas in previous readings from Rosling, West, Sen, another course, or from your experience. You have until 10:15.

I decided to look at CO2 emissions per person vs income. The growth for all countries was exponential with CO2 emissions increasing as income increased. This surprised me at first as most would think of countries such as India and China to have higher CO2 emissions, with the world’s largest populations and a rapid growth of energy production and consumption. However, countries with higher incomes, such as the United States, Canada, and Australia, all showed much higher CO2 emissions per person. This data reminded me of Rosling’s ideas of the significance of preconceived notions of developing countries and how they give us a skewed view of our world.

Another combination I found interesting was cell phones vs income in India, China, and the United States from 1995 to 2018. The x axis displays the GDP per capita while the y axis displays the total number of cell phones. The graph shows that as all countries grew economically, they also grew in terms of technological advancement and communication, and vice versa.

What I found surprising was the fact that too many countries in the drop down menu had limited or no data at all. Countries such as Ethiopia, El Salvador, and Yemen were all excluded from the data. This could be because only small percentages of these countries and regions have access to the internet or a mobile phone. As Blumenstock mentions in his article, a vast majority of developing nations are excluded due to the fact that in order to provide data, individuals must have cell phones.