DCI-102, Data in Humanities, course was one of the first “Data” Science classes that I took at Washington and Lee University. I have taken a statistics class. However, I did not have a full grasp of what “data” can be. The course opened my narrow definition of what data can be. Moreover, it taught me how to transform, visualize and interpret a wide range of data.
Although I am a neuroscience major at Washington and Lee University, I want to pursue a career in a football-specific industry. I am hoping to work as a coach or an analyst soon. I wanted to utilize this course to help me specialize in football-specific data analysis. With my narrow definition of what data can be, I initially wanted to look at more “number” based data for my final project: “how accurate is Adam Vinatieri?” However, lessons from the class changed my mind. I had worked with not only numbers but also text, images, and human networks. I realized my final project does not need to be number-based. I decided to step out of the box and to explore the network of contemporary NFL Head Coaches.
To understand the current NFL Head Coach network, I had to 1) search and gather data on each head coach’s coaching career, 2) create a dataset and transform and manipulate the data set to be suitable for visualization, 3) identity and interpret the patterns found in visualization and 4) communicate my findings with my class and the professor.
I was unable to locate a publically available dataset about the coaching career. However, I found a website (www.pro-football-reference.com) that had a page dedicated for all coaches who had held a “head coach” position in the NFL. Hence, I manually gathered all the information such as years, teams, and colleagues.
With all the information gathered, I created a dataset to have a single file that contains all the information. The visualization tool that I decided to use, Gephi, required a dataset to be formated specifically. Hence, I had to transform my existing data frame to match the specific format. Transforming the dataset was very difficult and required multiple trials.
Using Gephi I not only could visualize the human network between the coaches but also could select which criteria that I wanted to look at. For example, I could illustrate the network of coaches with a .500 or better record.
Lastly, I had to present my illustrations, findings and interpretation of such findings in front of the class. The class was composed of some people who know football and NFL but had more people who did not. Therefore, I had to inform a niche topic on both experts and laypeople.
Therefore, I believe that the DCI-102 Data in Humanities have helped accomplish the goals of the minor and six competencies. The course not only allowed me to dive into an industry that I want to be involved in but also enlightened me on what “data” is. Lastly, every part of my final project on visualizing the network of current NFL head coaches involved six-core competencies of data science minor.
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