After choosing the cities, the neighborhood may be the next level that users of Airbnb may consider. Hence, how to choose the neighborhood within the cities can be a nice question to explore in terms of data visualization. Here, we still use the Airbnb dataset of three cities, including Brussels, Antwerp, and Ghent. In the dataset, we try to use some variables related reviews (such as the number of reviews and different kinds of review scores) to help users to choose a neighborhood (See the following plots).
Those plots are interactive. When users go to Brussels, they can first check the number of reviews for each neighborhood, they brush some points based on the value that they want and then they can scroll to the left direction to see the review scores respectively. The review score includes information accuracy, cleanliness, check-in, communication, and location. Those scores are summarized by average value in terms of the room type and neighborhood. Guests can also make selections based on the single room type. When they click the points, the information with the single room type will be presented. Besides, when guests move the mouse to the single points, the popup will show the exact value of those points, including the name of the neighborhood, the room type, and the respective value. The following screenshots give relevant information.
