Population of South America

In this map series, I decided to map the population by country of South America. By doing this, I not only represented the Population by millions of each country, but I also decided to add a new field on the attribute table to represent the Population Density (Population per Square Mile). All the data was taken from the ArcGIS Database found on this computers. I worked with the "World" folder and decided to use the Country02 shapefile. These data is represented with the South America Lambert Conformal Conic Projection.

For the first map I used a simple Natural Breaks Classification with the gradual colors simbology. With Graduated colors, colors change according to the values of each country's population, using a color ramp with darker colors representing higher numeric values. This displays the Population by million of each South American Country. As we can see, Brazil has far more population with more than 151 million people compare with the small countries of Guyana and Suriname which have less than 1 million. I chose this classification methos since it works well with data that is not evenly distributed such as this one.

For the second map, I mapped the Population Density by square mile using graduated colors with a color ramped display. With this, each country is assigned a color depending on their classification and for this I used the natural breaks class (for the same reason as above). As we can see in this map, even though Brazil is the most populated Country, it isn't the most dense since it has a big area. With this map, we noticed that the most densely populated country in South America is Colombia (which is the second most populated one).

Finally, for the third map I used a Proportioned Dot classification to represent again the Population Density per square mile. In this display the data is cleanly represented by a single dot which varies in size depending on the density of the population. This representation is good for it shows different sized dots depending on the density, however it can be difficult to distinguish the different size dots since they are similar as well as to truly know what the actual density is. This display is better to give a glance of the data graphically but not explain it in detail.