Analysis of UC Admissions by Source School

Updated 9/2/18: Created function to add traces so that you can isolate data by county

I wrote a function to add traces so that you can isolate the data by county — in this new version, you can double click on any one of the county’s names to only look at the data for high schools in that county.

Updated 8/24/18: Started analysis of students who enrolled into UC system, created preliminary graphs using pandas and matplotlib.

Above, you can see the first iterations of this project. I began by creating bubble plots in matplotlib where each point represents a high school, and the size of each point is correlated to how many students from that specific school enrolled in UC schools and UC Berkeley, respectively. Both graphs indicate a similar trend — generally, high schools in cities with a lower median household income have a greater percentage of students who are eligible for free or reduced-price meals, which makes sense. It doesn’t appear that students in higher income brackets enroll more than others, but I’ll be looking into these datasets further to see if the same trends are observed for students who applied to the UC system, and for students who were accepted.

I then switched from matplotlib to plotly, in the hopes of creating a more interactive infographic. Using the same data as before, I created the following visualization.

Again, each point represents a high school and the size of each point is correlated to how many students enrolled in a UC campus. Now, you can mouse over each point and see which high school the point represents. I also added color so that high schools from the same county are colored the same.

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