cse442's Introduction
Name: Trevor Shibley UW Net ID: 1539742 CSE ID: tshibley My visualization was aiming to discover if there was a difference in population balance between men and women in the 1900 census vs the 2000 census. Basically - for every age group, are there more men or women in that age group for that census year? My guess was that for both years of the census, there would be more women than men in each age bucket, since women tend to live longer. This turned out not to be the case! (And I'm actually fairly curious to know why) To make the visualization, I first processed the data and made two seperate sets, with the data on the difference in the number of men and women for the year 1900 and the year 2000. I then used these data sets to make two seperate bar charts. I chose bar charts since they are a simple and common visualization that works well for displaying an age set like this where you want the viewer to be able to quickly pick out the trends. I chose to put the data in two seperate graphs rather than in the same graph with color coding since I think it does a better job of displaying the overall trend, and it makes it easy to spot the difference (like the huge increase in women over men in later ages in the year 2000 census). Putting them in the same graph looked too visually busy. I also made the decision not to normalize the data in any way, just using the raw difference between number of men and women. I went in to the visualization planning to use the ratio or something, but since the range of numbers were actually close the same, I left it in the raw number of population. This might underplay some of the differences in the 1900 census - but it also makes it easy to see the big picture (like the fact that just not that many people were alive past age 80 in the year 1900!) I left the data sorted in the natural age order since it's the most interesting axis to sort the data on, and it's the natural arrangement that the viewer would expect. The color of the bars is purple for no particular reason - I didn't want to make the visualization too busy and there wasn't some other aspect of the data I was trying to encode, so I didn't want to distract the viewer by changing the color at all. I choose the horizontal bars for the y axis at 1.5 million, 1 million, 0.5 million, and -0.5 million since they fit the data really well and added context without making the graph too visually busy. The negative positive split made the most sense for the data since their could be either more men or women, and making the more men bars grow down made it really easy to see the overall trends and kept the data flowing left to right across the age range.
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