25 Visualizations - One Data Set

A recent project by designer Nathan Yau demonstrates the importance of addressing the questions that a visualization answers about a certain data set. He took data from the World Health Organization about changes in life expectancy by gender and country from 2000 to 2015, and made 25 different visualizations based on this one data set. It was interesting to see how each visualization emphasized such aspects of the data set, and taught me how important it is to be intentional about the questions I want to answer with my own visualizations. 

Below are two visualizations that I believed were very successful in communicating the information that was intended. 

 This visualization immediately communicates the differences between the countries with the highest life expectancies (those that are above average) and the countries with the lower life expectancies (those that are below average).

This visualization immediately communicates the differences between the countries with the highest life expectancies (those that are above average) and the countries with the lower life expectancies (those that are below average).

 This visualization illustrates the dramatic change in life expectancy for one country in particular (Haiti) and would be appropriate only to communicate that drastic change for that specific country.

This visualization illustrates the dramatic change in life expectancy for one country in particular (Haiti) and would be appropriate only to communicate that drastic change for that specific country.

Click here to see the complete set of visualizations. 

Click here to read the article from WIRED (I highly recommend, it has some great insight from Yau about intentional datavis).