Transforming Data in Python with pandas: Part I

Description

Prerequisites: Participants should be familiar with basic programming concepts, including variable assignment, data types, function calls, and installing packages or libraries. Data Services' "Introduction to Python for Absolute Beginners" workshop or other introductory experience in Python or R will be especially helpful for this workshop.

This beginner-to-intermediate workshop is part one of a two-part workshop series on the pandas library, a popular Python library for data cleaning, data wrangling, and data analysis. Participants in this interactive class will use Jupyter Notebooks software and Python code to import, understand, and prepare a dataset for further analysis or visualization.

By the end of this workshop series, participants will be able to:

• Identify and use the two primary data structures of the pandas library: Series and DataFrame
• Implement functions from the pandas library to explore and analyze a dataset, including handling missing data, filtering and sorting data, grouping data, and calculating basic summary statistics
• Find documentation for the pandas library to troubleshoot errors
• Apply new functions to analyze a dataset