Data Wrangling in Python

"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 using mostly the data wrangling tools of the Pandas package. Pandas is a collection of functions/methods for working with data similar to R's tidyverse.

This course will cover importing data, cleaning data, creating and transforming variables, merging data, and plotting. It is a hands on class with time devoted to practicing using these tools to ready data for analysis. It is designed to prepare you to do research using pandas. It is designed for people who have no experience with Python and pandas, Python users who would like to learn pandas will also benefit from the class. Graduate students who will work in Python and pandas may choose to take this course at the beginning of their graduate student career or wait until they're ready to start doing research.

Note: for the section in Grainger Hall, we will email the room numbers as soon as they are available.

Instructor: Banghart
Room: 3218 Sewell Social Sciences Building
Dates: 8/19, 8/20, 8/21, 8/22, 8/23
Time: 9:00 - 1:00

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.