In Part 1 I discussed lying with charts. Now, in Part 2, I illustrate that lying with maps is also possible.
Map 1 includes a breakdown of the percent of minority students in school districts, in Hartford and surrounding towns. Map 1 was created by using Google Fusion Tables to merge two data tables together. One table consisted of the breakdown of minority students in each school district. The other table contained census data for each Connecticut town. Once the two tables were merged into one table, I altered the map style. For Map 1, I created color based categories to represent certain percentages.
Percent minority students in Hartford-area school districts, 2009-10
Click the map to view underlying data (Sources: CT Dept of Ed, MAGIC UConn Libraries)
Map 1 Legend (Source: Google Fusion Tables)
In the Map 1 Legend, you can see the five categories. Based on these categories, Map 1 illustrates that there was racial diversity among the school districts. When creating maps, the selection of categories can influence how data is illustrated. To really understand why this is true, let’s take a look at a second map that was created using the same two original data tables.
Percent minority students in Hartford-area school districts, 2009-10
Click the map to view underlying data (Sources: CT Dept of Ed, MAGIC UConn Libraries)
Map 2 Legend (Source: Google Fusion Tables)
Map 2 was also created using Google Fusion Tables and the same two original data tables that were used for Map 1. However, Map 2 illustrates sharp racial divisions among school districts in the Hartford area. But, how can this be true when the exact same data was used to create both maps? Just like with charts, the way you choose to display data in maps makes a big difference. Recall that in the Map 1 Legend I used five categories for my legend. Now notice that in the Map 2 Legend, I used only three categories. Using less categories made the map appear to have drastic differences between more towns.
In addition, you may have noticed that I defined the categories for each of the legends using two different sets of percent breakdowns. The cut off percentage for each category can be very influential in determining which category each district falls under. Since most of the towns shown have less than 35% minority students in their school districts, more towns appear to have little diversity. This choice of categories also depicts that there are much more minority students in the center of the mapped area.
When creating maps, and charts, it is important to consider the scales and categories that are created with them. Changing scales and categories can allow you to show one set of data in multiple ways. In other words, lying with charts and maps is most certainly possible.