For this “data interview”, I decided to work with a dataset from the Wisconsin Elections Commission. It’s a website I discovered when I took a class reporting trip to Waukesha, Wisconsin during the 2016 election season. There were a few datasets to choose from and I chose one on the 2016 Presidential Election Results by Ward. As the name suggests, this spreadsheet breaks down the presidential election results by candidate but also by county, municipality and political districts. It’s a pretty large amount of data to deal with, so the comparison I make will be a little more on the smaller side, just to keep things manageable. The first comparison I thought to make was to take the number of votes for the major candidates, Donald Trump and Hillary Clinton and see how many votes the two of them got in each individual county.
Seeing as he won, I decided to look at Trump’s numbers first. I put together a pivot table that isolated Trump’s votes and the numbers per county. The results I received were interesting. Trump got the most votes in Waukesha County, a known Republican stalwart in the state. In that county, Trump received a total of 142,543 votes. His lowest returns came from Menominee County with a small 267 votes. That’s a difference of 142,276 votes. Overall, Trump received a total of 1,405,284 votes from the state of Wisconsin, taking home the Republican Party’s first presidential win there since Ronald Reagan.
I decide to take a look at this data through a more visual method, so I attempted to make a chart which is included in my spreadsheet. I would say that the numbers overall are so different and so numerous that it doesn’t really lend itself to a chart. It makes the display much too cluttered to be useful. The only solution I could think of is if you leave some information out in order to make the amount more manageable. The problem with that is that you’re not getting the whole picture.
Next, I repeated the same process for Hillary Clinton’s vote totals as well. I used a pivot table to find the data I needed and then sorted in the way I needed. What I found is that Clinton’s highest vote amount came from Milwaukee County with 288,822 votes. The lowest amount came from Florence County with 665 votes. That results in a difference of 288,157 votes. Overall, Clinton took home 1,382,536 votes total. Which means, Clinton lost to Trump by a difference of 22,748 votes.
Once again, I created a chart from the data for Clinton like I did with Trump in order to see what insights I could gain. Like with the Trump data, I think adjustments would need to be made to the quantity of data in order for a chart to be useful.
Overall, I found this to be an interesting exercise. I discovered new information about the 2016 election that I didn’t already know and couldn’t readily find in a news source. The dataset goes even more detailed into the other candidates. It’s data that could be useful for someone analyzing the effect of third party candidates in swing states, which has frequently been a hot topic in political circles. My spreadsheet can be found at this link