LIS5318 Visual Analytics

This week we were introduced to the visualization dashboard application Plot.ly. I created several plots using the data provided by the instructor, which had two dimensions or variables, average position and time.  First, I created two pie charts to represent the relationship of each data point of both the average position and time in relation to the sum of each set of data:  While these pie charts represent the proportion of each value to the whole or sum of the values, it does not give us a very good representation of the two dimensions in relation to each other. Additionally, the categories in the legends do not correspond to meaningful aspects of the data. The pie chart function of Plot.ly therefore does not express meaningful relationships between the graph and the legend. Further, a drawback of the export function is that the legend is cut off near the bottom, so it cannot be used to effectively interpret the pie charts. Otherwise, the colors of the pie chart are very vi...

The following visualization was developed using data from the United States Department of Transportation Federal Transit Authority. The FTA supports public transportation within the United States.  This visualization represents four measures of data, representing the Dallas-Forth Worth-Arlington, Texas metropolitan area, spanning 2014 to 2018.  Some points of interest in this data are the number of collisions with motor vehicles in 2015 (142), and the number of collisions with persons in 2016 (13). Of the data I reviewed from the FTA dataset provided by the instructor, DFW-Arlington appeared to be an outlier with regard to these plot points.  Both the number of collisions with motor vehicles and the number of collisions with persons declined by 2017, however the number of collisions with persons rose again in 2018. It does not appear that vehicle revenue hours or vehicle revenue miles correlate to the alarming number of collisions with vehicles and persons, as these value...

The following image represents a focus on using color, line, shape, and contrast to exemplify certain aspects of the map made in module 2. Using vectors in Adobe Illustrator, I created a visualization that features prominent elements of Floridiana, including a text box that highlights one aspect of the data that can be seen on the map.   

The following visualization (which can be interacted with here: https://tinyurl.com/publichousinginflorida) was developed based on Housing and Urban Development data for public housing developments in the United States, updated in December of 2023. The visualization represents the average household income (size of the marks) and average rent (shade of the marks) for each development in the state of Florida.  The dataset used for this visualization contains many variables, including number of occupied dwellings and vacancies, percentage of demographic groups in each development (Native American, Hispanic, female head of household with and without children), among many others.  Initially, I found it difficult to organize the visualization, because my impulse was to create pie chart markings based on occupancy. However, this proved difficult. This visualization is the result of a compromise I made with myself to represent some aspect of the data without thinking too hard about ho...