Analysing relationships

In this first exercise you are tasked to analyze pricing patterns in Airbnb data to inform strategies for optimizing revenue and meeting customer preferences.

Every new session starts with the cleaned airbnb_combined table already in place, so you can query it straight away. If a query reports that airbnb_combined or standardized_neighborhood_group can't be found, the hint has a statement that rebuilds the table.

In this exercise, you will use SQL to calculate key pricing metrics—minimum, maximum, and average prices—for different room types. This analysis will help you identify which room types command higher prices and uncover trends in pricing variability.