Fall 2020
INF 385T.09 Special Topics in Information Science: Data Wrangling
Synchronous online class meetings along with additional asynchronous online coursework.
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
COURSE NOTES
previous syllabus: https://howisonlab.github.io/datawrangling/index.html
PREREQUISITES
Graduate standing.
RESTRICTIONS
Registration priority given to iSchool students. Additional seats may open up for outside students in a later registration period.