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:
While static plots are excellent for publications, interactive visualizations are essential for data exploration and sharing research with a broader audience. This workshop teaches you how to make data interactive. We will focus on the Plotly ecosystem and Streamlit to create "live" data environments. You will learn how to take pandas DataFrames and NetworkX graphs and turn them into interactive applications that respond to user input in real-time.
Topics Include:
- Interactive Geometry: Creating "hover-ready" charts (scatter, line, and bar) where data points reveal underlying metadata.
- Network Interactivity: Exporting NetworkX objects into interactive web-based graphs that allow for zooming, dragging, and node-filtering.
- The Grammar of Widgets: Adding UI elements like sliders, checkboxes, and dropdown menus to control data subsets dynamically.
- Layout and Design: Organizing multiple plots into a coherent dashboard layout using Streamlit columns and containers.
- Sharing Your Work: Brief overview of deploying your interactive app to the web using cloud hosting services.
Contact information:
Please email mrsmith@rice.edu if you have questions about the Data@Rice workshop series.
For more information about Python and other data courses at Rice, visit https://library.rice.edu/services/data-workshops, or contact researchdata@rice.edu.
Course Materials: