Spreadsheet Modeling and Wrangling with Python
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| Titel: | Spreadsheet Modeling and Wrangling with Python |
|---|---|
| Sprache: | English |
| Autoren: | Mark W. Isken (ORCID |
| Quelle: | INFORMS Transactions on Education. 2025 25(2):152-168. |
| Verfügbarkeit: | Institute for Operations Research and the Management Sciences (INFORMS). 5521 Research Park Drive Suite 200, Catonsville, Maryland 21228. Tel: 800-446-3676; Tel: 443-757-3500; Fax: 443-757-3515; e-mail: informs@informs.org; Web site: https://pubsonline.informs.org/journal/ited |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publikationsdatum: | 2025 |
| Publikationsart: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Spreadsheets, Models, Programming Languages, Monte Carlo Methods, Computer Software, Data Analysis, Data Collection, Engineering, Business Education, Business Schools |
| DOI: | 10.1287/ited.2023.0047 |
| 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. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Dokumentencode: | EJ1462226 |
| Datenbank: | ERIC |
| 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. |
|---|---|
| DOI: | 10.1287/ited.2023.0047 |