Visual Analytics LIS 4317

For this assignment, I decided to use a simple line graph because I felt like it depicted the results of the excel file the greatest. The six variables that I decided to work with were the collision with motor vehicle, collision per person, ridership, vehicle revenue, vehicle revenue miles, and primary UZA sq miles because I felt like they were the most important variables in the dataset. When working on the graph, I initially attempted to use the city names as my column values. I quickly realized that this would result in a graph that was much more difficult to read, so I went with years instead. With this graph, readers can quickly see that the results increased up until 2014 then stayed constant from 2015 to 2017 to then declined in 2018, and continue in 2019. https://public.tableau.com/app/profile/jahnae4791/viz/Module4_16750831980210/Sheet1

To make this graph more pleasing, I added a title with some graphics to add more context to what the colors represent. I considered adding a US flag but decided that having the red, white, and blue I voted sticker was enough. I also included the states with the highest and lowest turnout rates so that the reader can understand that the darker the color, the more turnout they had.

For this assignment I decided to use a dataset called 2020 US General Election Turnout Rates, this data was a csv file and included many facts about the 2020 election voter turnout, such as the number of people eligible to vote, percentage of turnout rates, people within the voting age, amount of ballots counted, and much more. For this visualization, I will be looking into the number of ballots counted.  Initially, I planned on using the point function in Tableau to visualize the different ballots counted, but I found that the differences were slightly harder to read in comparison to using color to show the different voter turnouts. Having the key to the side showing the least and most ballots counted helps readers to understand what lighter versus darker colors mean. Something else I could have added to this graph is the name and number of ballots for each state. I decided to not add this because I felt like it made my visualization less pleasing to look at, the data itself ...

The visual analytics that first caught my eye was the Florida coronavirus visual dashboard. This is because this dashboard takes the complicated information about the coronavirus and makes it simple so that the average person can read it and understand what it is saying. If the governor were to release the raw document with only the numbers, it would be harder to get the information across. This dashboard includes the data, which is the number of people who are currently affected by covid. The visualization of what areas are most affected on the map of Florida and the graphs showing the number of deaths and new cases. This helps people gain knowledge about the coronavirus in Florida. Overall this visual does a great job of introducing new information in a simple form.