Prerequisites:
Knowledge of Python, including completion of Data Analysis and Visualization with Pandas and Network Analysis and Visualization with NetworkX, or equivalent experience with Python data structures and Matplotlib.
Overview:
Prerequisites:
Familiarity with the research process and basic knowledge of Python. This workshop is specifically designed for researchers who find manual coding a bottleneck in their data analysis, simulation, or visualization workflows.
Overview:
Prerequisites:
Recommended for those who have completed the 2-part Python Fundamentals series or who have basic Python skills and familiarity with data structures like dictionaries and lists. Prior experience with HTML may be helpful but isnot required.
Overview:
A vast amount of data for research and analysis is stored in unstructured formats across the web. This workshop introduces participants to the essential techniques for "web scraping"—the process of programmatically extracting data from websites.
Prerequisites:
Recommended for those who have completed the 2-part Python Fundamentals series or who have basic Python skills and familiarity with data structures like dictionaries and lists.
Overview:
This workshop introduces the fundamental concepts of network analysis using NetworkX, the standard Python library for the study of networks. Participants will learn how to represent relational data—such as social networks, citation maps, or transport systems—as mathematical graphs to uncover hidden patterns and structures.