In this post, I will be analyzing the AirBnB Dataset using visualizations. For analysis, I will work on data from Beijing.
I want to answer the following questions from my data exploration:
- How many room types are in Beijing? Which one has more listings?
- What is the price range between the room types? Is there a huge difference between them?
To help us understand the data, let’s load in the Dataset, and explore its characteristics through visualizations.
Visualizations
We will first look at the scatterplot of the Location of the room types in Beijing. We can use variables between longitude, latitude, and price.
We can see there are three room types in Beijing. We have more choices between the entire home/apartment and private room. The entire home/ apartment has the most listings and, like the private room, they are spread out across the whole city. On the other hand, the shared rooms only have a few listings.
Next, we will look at a bar chart of the price of the room types.
From the graphic, we can see the entire home/apt costs more than the other two room types. It costs almost 1/3 more than the private room and it almost doubles the shared room price.
Through our data visualizations, we answered two questions about the Airbnb dataset of Beijing. First, we discovered that there are three types, and the entire home/apt appears the most. Secondly, the prices range from 350 yuan to 850 yuan.
