Python is rapidly becoming the programming language of choice for scientific research, and Jupyter Notebooks provide a user-friendly way of writing and running python code and of teaching and learning how to program. Visual analytics is playing an increasingly important role in data science by allowing researchers to explore massive amounts of data for patterns which may not be obvious using other methods.
In this webinar, we will briefly review data visualization principles and practices and jump into a series of data visualization examples using Python libraries including pandas, matplotlib, bokeh, seaborn, and networkx.
Data Visualization With Python Using Jupyter Notebooks
Comet Webinar: Data Visualization With Python Using Jupyter Notebooks
Remote event
Instructor
Jeff Sale, M.A
XSEDE ECSS Visualization Consultant and SDSC Learning Design Technologist
Jeff Sale is an XSEDE ECSS visualization consultant who enjoys exploring novel visual analytics approaches to spatiotemporal data. He also works as a Learning Design Technologist at the San Diego Supercomputer Center promoting the use of cyberinfrastructure within the K-12 and higher education HPC communities through workshops, training, and curriculum development in collaboration with a talented group of experts and educators.
