We were interested in looking at the factors that affect student performance and how they determine the success of students throughout grade school and high school. Do these factors change over time or remain the same? That is an example of a question that we sought to answer. We utilized data sets that span the years 2011 to 2013 and include information on elementary, middle, and high schools. In addition to this, the topic was of particular interest to us because a member of our group went to a public high school in the Chicagoland area, making our research particularly important to our team. Another member of our team had worked with the Louisiana Department of Education during high school and is passionate about the use of data analytics to improve the lives of students from underrepresented communities.
Our journey started with searching for a data set that might inspire our project. We found the 2011 Chicago Public Schools data set, which immediately became of great interest to us. It had a substantial amount of data from student performance in algebra to family involvement. After choosing this as our focus, we decided to expand upon this by including another data set: 2013 Chicago Public Schools data set. This set includes less schools in total but includes more high schools than the 2011 data set, which allows us to expand our focus a bit. It also enables us to take time into consideration.
We utilized the requests library to get our data from the website before performing some data cleaning on both sets, which will be detailed in the Data Sources page of this website. From this, we moved onto our visualizations. For these, we focused on metrics related to a students performance such as four year graduation rate and students passing algebra. We then took data such as teacher attendance and suspensions to see how these values factored into student performance. After creating the visualizations, we grouped similar ones together and implemented them into this website.