Case Study

Oklahoma Travel Management Program: Performing Differential Analysis Excel or with Pandas

Learn how to merge a list of manually prepared categories with a large dataset of purchasing card transactions (400,000+) using Excel or Pandas for usein a differential analysis activity.

Published

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About this case study

This case is designed for students to work with real data to perform differential analysis. Using data from the state of Oklahoma, students are tasked with determining whether the state should create a centralized travel management program. The costs of establishing and operating a centralized department must be weighed against potential savings. Students manually categorize Merchant Category Codes (MCCs) into one of six travel expense categories and then merge these categories back into the larger dataset for use in the differential analysis. The case can be completed using either Excel or Python.

Authors

How to cite

"Oklahoma Travel Management Program: Performing Differential Analysis Excel or with Pandas" by Michael Penn Jr., Ye Joo Park and Justin Stearns. University of Illinois-Deloitte Foundation Center for Business Emerging Technologies. https://emergingtech.giesbusiness.illinois.edu/distributed-content/performing-differential-analysis-with-data-merged-in-excel-or-with-pandas/. Licensed under CC BY-NC-SA 4.0.

Materials are shared under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license.

University of Illinois-Deloitte Foundation Center for Business Emerging Technologies
Champaign, IL 61820
Email: EmergingTech@business.illinois.edu
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