Repository of my python notebooks. Consists of data analysis and scientific computing work
Scientific computing/exploratory visualizations for advanced macroeconomic theory regarding trade offs between consumption and leisure. In short, how can consumers optimally split their time between working (for the sake of consuming their income on goods and savings) and rest, or leisure?
An NLP project implementing a semantic parser based off of a classical semantic theory known as File Change Semantics. A context free grammar is created and used to generate some sample sentences, which are then parsed. Applications to psycholinguistics are discussed, especially with regards to algorithm efficiency analysis.
A linear regression is performed on the mortality rates across US states by looking at various independent variables: adult obesity rates, opiod sales, political leaning, and average age. While this analysis is largely cross sectional, a panel data analysis is glanced upon by comparing 2016 data to 2008 data to see if the same variables are equally powerful explainers a decade prior.
As the pandemic wore on, hybrid and in-person classes were becoming more popular again at Rutgers. But different departments offered in-person classes at different rates. data from Rutgers's Schedule of Classes is scraped and visualized to see how different departments responded to the pandemic. A bit of a tutorial is included as well.