Pre-requisites: Participants should be familiar with basic programming concepts, including variable assignment, data types, function calls, and installing packages or libraries. Introductory experience in Python or R will be especially helpful for this workshop. 

This beginner-to-intermediate workshop is 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  
  • Calculating basic summary statistics  

Find documentation for the pandas library to troubleshoot errors and apply new functions to analyze a dataset.  

Instructor(s): Lubov McKone

Registration link: https://jhu.libcal.com/event/15071712