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Spreadsheet Modeling and Wrangling with Python

Author

Listed:
  • Mark W. Isken

    (Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, Michigan 48309)

Abstract

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and data-wrangling tasks. In addition, students are exposed to basic software engineering principles, including project folder structures, version control, object-oriented programming, and other more advanced Python skills, creating deployable packages and documentation. The module is supported with Jupyter notebooks, Python scripts, course web pages that include numerous screencasts, and a few GitHub repositories. All of the supporting materials are permissively licensed and freely accessible.

Suggested Citation

  • Mark W. Isken, 2025. "Spreadsheet Modeling and Wrangling with Python," INFORMS Transactions on Education, INFORMS, vol. 25(2), pages 152-168, January.
    • Handle: RePEc:inm:orited:v:25:y:2025:i:2:p:152-168
    DOI: 10.1287/ited.2023.0047
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    References listed on IDEAS

    as
    1. Mark W. Isken, 2003. "Data Cleansing and Analysis as a Prelude to Model Based Decision Support," INFORMS Transactions on Education, INFORMS, vol. 3(3), pages 23-75, May.
    2. Kenneth Baker, 2000. "Gaining Insight in Linear Programming from Patterns in Optimal Solutions," INFORMS Transactions on Education, INFORMS, vol. 1(1), pages 4-17, September.
    3. Cliff T. Ragsdale, 2001. "Teaching Management Science with Spreadsheets: From Decision Models to Decision Support," INFORMS Transactions on Education, INFORMS, vol. 1(2), pages 68-74, January.
    4. James R. Evans, 2000. "Spreadsheets as a Tool for Teaching Simulation," INFORMS Transactions on Education, INFORMS, vol. 1(1), pages 27-37, September.
    5. David L. Alderson, 2022. "Interactive Computing for Accelerated Learning in Computation and Data Science," INFORMS Transactions on Education, INFORMS, vol. 22(2), pages 130-145, January.
    6. Aaron Babier & Craig Fernandes & Ian Yihang Zhu, 2023. "Advising Student-Driven Analytics Projects: A Summary of Experiences and Lessons Learned," INFORMS Transactions on Education, INFORMS, vol. 23(2), pages 121-135, January.
    7. Stephen G. Powell, 2001. "Teaching Modeling in Management Science," INFORMS Transactions on Education, INFORMS, vol. 1(2), pages 62-67, January.
    8. Peter C. Bell, 2000. "Teaching Business Statistics with Microsoft Excel," INFORMS Transactions on Education, INFORMS, vol. 1(1), pages 18-26, September.
    9. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
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    11. Robert L. Carraway & Dana R. Clyman, 2000. "Integrating Spreadsheets into a Case-based MBA Quantitative Methods Course: Real Managers Make Real Decisions," INFORMS Transactions on Education, INFORMS, vol. 1(1), pages 38-46, September.
    12. Sam Savage, 2001. "Blitzograms---Interactive Histograms," INFORMS Transactions on Education, INFORMS, vol. 1(2), pages 77-87, January.
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