The Epidemic of Unemployment

Beta Release Prototype:

Visualization Description:

This visualization is a very simple one, but the reasoning behind this is because it will not stand alone. My goal for this visualization is to show the change in unemployment rates for different racial groups over time. My goal for this visualization is for it to accompany my Alpha Release Prototype in a particular manner. When the user clicks on a particular part of the map in the Alpha Prototype, I want it to highlight a corresponding line in this graph. Thus making the two visualizations cohesive. One would provide general information regarding unemployment within the particular, user-selected state, and the line chart would show the trend of racial unemployment within that state.

In addition, the data for this prototype is not extremely complex, but I plan on aggregating more complex data to make a richer visualization for this prototype.

Planned Interactivity:

There are two primary features of interactivity that I am aiming to integrate:
First, a hover feature. When hovering over specific points on the line graph, a tooltip will appear and display statistics including: the rate of unemployment, the race it is representing, etc. Overall providing a better understanding of the specific state's trends.

Secondly, a brush feature. What I mean by this is a feature that allows the user to choose a line in which they wish to view and the surrounding lines will grey out and only highlight the selected line. Thus providing the user with greater ease for viewing and understanding data.

Prototype Design:

I used Tableau for my prototype. The data used here allowed Tableau to automatically generate axis for years, races, and the rate(s) of unemployment. The year is used for the column values and unemployment rate is used for the row values. This then allows for great ease when making a line graph such as this where the colors represent the varying unemployment rates throughout.

Prototype Feedback:

Feedback for this prototype was short and simple: fix the colors, fix the axes, add more data.

To fix the colors, I went with a more diverging theme in my implementation in order to showcase the differences between each of the respective groups.

Rather than having multiple axes for each group, every peer suggested I move all the plots into one axis. After accomplishing this, I shortened the timespan to fit my final goal and made it from 1999-2017.

Lastly, adding more data. Many peers were interested in seeing more racial groups than just the four that were listed. In my final implementation I added a few additional racial groups to provide a more interesting viewing experience. In addition, a peer was concerned about the lie factor of my data because unemployment in my primary visualization was calculated by thousands, but the original dataset I had found for this visualization was on a scale of ten-thousand.

That was one of the more helpful pieces of advice I received, so I searched to find a dataset that was on the same magnitude as the other.