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Identifying trends and patterns in fuel costs & usage from credit card transaction data

-Rishabh Mulani, Krzysztof Dutka, Nanyi Yang

(All the visualizations are interactive! Hover your mouse over to see additional info!)


With a prelimiary analysis, we were able to understand that our data was primarily about Champaign county, with some info about neighbouring counties (even in different states This plot shows a count of transactions per county, and we have data about 6306 transactions in Champaign

This plot helps us understand how average unit costs varied by county. While most counties fall within an average unit cost range, some counties like Clinton, Grundy and Hendricks (Indiana) have recorded the highest average unit costs

This is a really interesting plot as, when you hover over a point, it shows you the name of the merchant with that average unit cost. With this, it becomes easy to analyze which merchant brand is charging a higher premium in a specific location. This also helps understand whether a relationship exists between number of transactions and unit cost for a brand to see if more transactions attracted brand to charge a higher price. That assumption did turn out to be true as some brands have been seen to charge a higher premium based on their popularity.