The tasks for the first lab are: 1. Read the NYC postal areas in Shapefiles into sf objects. 2. Read and process the NYS health facilities spreadsheet data. Create sf objects from geographic coordinates. 3. Read and process the NYS retail food stores data. Create sf objects from geographic coordinates for NYC. 4. Use simple mapping method such as mapview with a basemap to verify the above datasets in terms of their geometry locations. 5. Save the three sf objects in a RData file or in a single GeoPackage file/database.

This project combines exploratory data analysis, dimensionality reduction, clustering, and predictive modeling to analyze soccer match data and predict outcomes. The results provide valuable insights into team performance and the factors influencing match results, with potential applications in sports analytics, betting, and team strategy development.

Does offering an enological experience impact Airbnb ratings, and is this moderated by Superhost status?