This workshop has sessions on multiple days. You should plan to attend all the sessions.
"Data Wrangling" is the process of preparing data for analysis, which includes importing, cleaning, recoding, restructuring, combining, and anything else data needs before it can be analyzed. Data wrangling is a critical skill for research. This course teaches wrangling skills, mostly using the data wrangling tools of the Pandas package in Python. Pandas is a collection of functions/methods for working with data comparable to R's tidyverse.
This course will cover importing data, cleaning data, creating and transforming variables, merging data, and basic data visualization. It is a hands-on class with time devoted to practicing using these tools to ready data for analysis.
Almost all students should take Introduction to Python for Data Analysis prior to this course.
(The section scheduled 10:00-3:00 will take a one-hour break for lunch at roughly noon each day.)
Room: 3218 Sewell Social Sciences Building
Dates: 5/23, 5/24, 5/25, 5/26
Time: 10:00 - 3:00