Catalog Description
Instructor Description
Learning key data wrangling maneuvers in abstract and implementations in SQL, Excel, R Tidyverse, and Python Pandas. Maneuvers in data transformations include Nest, Pivot, Mutate (inc. separate/unite), Group/Summarize and Rectangling. Projects include working with "wild caught" data datasets (usually CSV or JSON) and computational notebook environments (e.g., iPython, Jupyter, Rmarkdown, Quarto). Fall 2024 has changes from previous syllabus now that we have Database Design and Introduction to Programming. Nonetheless, the previous syllabus is still useful as it links to course materials that show the teaching approach and type of assignments. http://howisonlab.github.io/datawrangling/#Schedule_of_classes
Prerequisites
Graduate standing.
Scheduled and Upcoming Classes for this Course
| Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
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| INF 385T.09: Special Topics in Information Science: Data Wrangling
James Howison Syllabus |
Fall Term 2025 |
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Past Classes for this Course
| Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
|---|---|---|---|---|---|---|
| INF 385T.09: Special Topics in Information Science: Data Wrangling
James Howison Syllabus |
Fall Term 2024 |
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| INF 385T.09: Special Topics in Information Science: Data Wrangling
James Howison Syllabus |
Fall Term 2023 |
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| INF 385T.09: Special Topics in Information Science: Data Wrangling
James Howison Syllabus |
Spring Term 2022 |
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