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INF 385T.09 : Special Topics in Information Science: Data Wrangling

Areas

Skills

Topics

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.

Instructor Topic Title Year Semester Syllabus
James Howison
2024Fall
James Howison
2023FallSyllabus
James Howison
2022SpringSyllabus

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