"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.
We will take a one-hour break for lunch at roughly noon each day.
Room: TBD Sewell Social Sciences Building
Dates: 6/21, 6/22, 6/23, 6/24
Time: 10:00 - 3:00
Each session of this class builds on the material taught in the previous sessions. If you cannot attend all of the class's sessions but still want to take the class, you must contact the Help Desk, find out what will be covered in the session(s) you will miss, and learn that material on your own before the next session. In most cases the material can be found in the SSCC Knowledge Base.
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