Hannah Aizenman led the time series/categorical data session. Using Pandas, a Python Data Analysis Library, Hannah demonstrated the flexibility of using a programming language to do data analysis. Unfortunately, my computer gave me a couple of hiccups and I spent too much time resolving them. Regardless, Hannah did a remarkable job on the topic. She also demonstrated the benefits of this software where a researcher gains efficiency in working with data but has to invest time in learning a programming language’s capabilities.
Ian Phillips led the afternoon session on databases using SQL. Ian reminded the participants that good research requires creating, updating, and accessing data on a reliable platform. He provided valuable examples of the basics of database design, development, and implementation. In sum, a good database provides the researcher with the foundation for her/his analysis.
Valuable lessons for all!