http://rpubs.com/cruzsanchezk/hh_final_f23
The two interactive line plots linked represent two different datasets. The Affording Carleton plot expresses the trends of the following variables: ‘Carleton Tuition Cost’, ‘Comprehensive Cost’, ‘Total Cost of Other Expenses’, and ‘Cost Due Post Aid’, all by year. The other plot, Carleton Admission by Race and Ethnicity, 2013-2021, was constructed with the proportion of demographic enrollment data by year.
I used R to project this data, specifically the Plotly library, to make interactive plots that can be modified to show data from a certain year range. The variables the plots display can also be changed by the user selecting which variables they want to see from the legend. These plots track the yearly data in a simple yet efficient format so we can observe the data trends effectively and readably. I also coded a range selector into both plots to allow users to access data based on the trends they want to observe for a specific date range.
7 thoughts on “FINAL PROJECT COMPONENT 3”
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I really like this visualization I think it is very helpful in identifying trends in tuition costs and the backgrounds of students on campus over time. The only thing I was confused about is what the Carleton tuition cost vs comprehensive cost entails and what is included in the “other expenses” category. Maybe if you included that below the graph that could be helpful. I really like how you included the option to compare the actual raw data for each category over time. Overall, I thought it was a very clear and insightful data visualization.
You did a fantastic job on the visualization. I love how the viewer is able to edit the x axis to narrow down the timeline. It is a little hard to see each category’s color on the race and ethnicity chart, but it definitely conveys the overall message.
This is a great visualization, the level of interactivity is impressive. I really liked the ability to scale the x axis. I also think the ability to turn off the different lines really helps the viewer to be able to zoom in. Like for the first graph when the white students line is active it is harder to see the differences in the other lines but if you turn it off you can see all the changes of those lines aswell.
This is a very interesting visualization. I think it’s cool that you can change the timeline you are looking at by changing the x-axis. I like that you can turn off different lines in order to focus on a specific demographic. It’s crazy how turning the white students line makes the graph look completely different, it really puts admission demographic percentages into perspective.
Super fascinating data visualization! The differences in the enrollment rates of different demographics are shown really starkly– definitely a super effective way to communicate a message. I wonder how the enrollment demographics data relates to national (or even Minnesotan) population demographic change. The tuition data visualization is also really effective– the bright pink of the “cost due post aid” really stands out from the other data, which is useful.
I really like the interactive elements of this visualization. The ability to turn on and off different variables and adjust the time window allows for exploration and clarity with your data, which is really nice. If you mess with the year scale too much it formats weirdly and can’t be reverted unless you reload the page, but that is definitely a problem of user error.
I really liked how your group was able to create a data visualization that was very visually appealing. I also thought you did a really effective job cleaning your data, it was straightforward to interpret. I also liked how you color-coded your graph, that extra touch made it very easy to interpret. Overall you guys did a great job.