Analyzing the Airbnb market in Munich

Using data to determine the best times of the year, areas, and accommodations that fit your holiday plans.

Skills: Python, Matplotlib, Seaborn, Data Visualization

Planning a trip can be a daunting task, particularly when considering price variations, host ratings, and pinpointing the ideal location to stay. By utilizing datasets from Inside AirBnb, I delved into the price and listing data for Munich. This exploration allowed me to uncover insights into price fluctuations throughout the year, differences in costs across neighborhoods, and the characteristics of various hosts. With these insights, my aim is to streamline and enhance your next travel planning experience, making it both informed and seamless.

Please see code availiable here.