A data visualization project for analyzing proportion of population below the international poverty line of US$1.90 per day between 1990 and 2013. (source: UNData.org)
Here are some graphics representing poverty rates of different areas across the world. The poverty rate at $1.90 a day is the proportion of the population living on less than $1.90 a day, measured at 2005 international prices, adjusted for purchasing power parity (PPP). Purchasing power parities (PPP) conversion factor, private consumption, is the number of units of a country’s currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. Further information on this proportion or poverty rates can be obtained from UNdata.org.
Each dot in the graph represents the poverty index of a region in a specific year. The denser clusters of dots in the lower y-axis (or bottom of the graph) concludes that poverty rates for majority of areas lie below index 20.
We represent each data by area and year in a cluster graph.
The top 5 countries with the highest rates of population living under $1.90 are Madagascar, Malawi, Guinea-Bissau, Zambia, and Rwanda. This clearly shows us that higher poverty rates dominate in African regions.
We use d3-tip, mouseover and mouseout function in order to create "hover" effects, that is, to hide/show information on the Country and Poverty Rates for each bar.
In our third graph, we combine ideas from the first graph with the second one, where we want to see how each of these 5 countries perform overall in all the observed years since 1990. Guinea-Bissau, Madagascar, and Zambia have a similar fluctuating pattern where poverty rates seem to decrease at a certain point and increased approaching 2010. On the other hand, Malawi and Rwanda share a decreasing pattern from the previous years. Note that the number of data gathered for each country may be different.
To make the top 5 countries stand out in colors, we lower down the opacity of circles representing other countries in the graph. We use .curve(d3.curveMonotoneX) to smoothen the colored curves that correspond to these top countries.
We see that data between countries across the years are consistent: Least developed countries have the highest poverty rate, followed by landlocked developing countries. Small island developing States come third, then developing regions come last with the least poverty rate. More data gathered between 2010 and 2014 results in thicker opacity on the circles.
We use d3.scaleSqrt() function to draw the proportion of these circles, and also scalePoint() to create an x-axis for categorical range of years.
Each line starting 0 degree (vertical) represents the year since 1990, and the year increases as the line moves in in clockwise direction. Each area or country is placed at certain radii from the center of the circle, indended to show that the poverty rate is higher as the country name moves away from the center. Equivalently, the closer it is to the center, the lower the percentage of that area's poverty rate. It is definitely interesting to see that those at the farthest points from the center are mostly African countries. This also validates our hypothesis in #2 that in fact African countries make up majority of the poorest areas in the world.
The radialLine() function is used in this graph, along with scaleLinear() and scalePoint() to draw the lines at certain angles and radius and color spectrum. It is actually pretty fun!