Analyzing the Boston Airbnb open dataset
AirBnb has taken the world by storm and has been making planning vacations in a new city exciting and invigorating. AirBnb has over 150 million users worldwide and 6 users check into AirBnb every second. Isn’t that amazing?
So, what better way to enhance this amazing service by analyzing data and the key trends.
Crisp DM is a strategy that is a key component to help us analyze the data better. Now, you might have the question, What is Crisp DM?
Crisp DM is known as Cross-industry standard process for data mining.
In this post, I will be analyzing the AirBnB Dataset using visualizations and learning models. For analysis, I will follow the CRISP-DM process, on data from Boston
I want to answer the following questions from my data exploration:
Q1. What time of the year has the highest rental prices?
Q2. What is the relation between price and property type?
Q3. Which type of room has the majority of listings in Boston airbnb?
Steps included in this process are
1-Business understanding.
2-Data understanding.
3- Data preparation.
4- Modeling.
5- Evaluation.
6- Deployment.
Data Understanding:
The data (available at Kaggle) has 3 files
- listings: Full descriptions and average review score
- calendar: Listing id and the price and availability for that day
- reviews: Unique id for each reviewer and detailed comments
-Check data (number of row and column)
-Check all columns in listings data set
-Provide a set of all columns with 0 missing values
-Check listings info and data type
Data preparation:
In order to better perform our analysis, we have cleaned the Price field of the listings data frame and converted it into a float
Business Understanding:
The most common logical questions that anyone would ask in order to make profit as a new AirBnb host or as a user of the service.
These are the common questions that we will ask to better analyze the service
Q1-What time of the year has the highest rental prices?
July month is time of the year has the highest rental prices
Q2. What is the relation between price and property type?
The following heatmap shows the average prices for each property type. The Shared room type is mostly the cheapest while the bed and breakfast property type is generally the cheapest
Q3. Which type of room has the majority of listings in Boston airbnb?
Entire home/apt has the majority of listings in Boston airbnb
Deploying:
https://github.com/Leenaalshaibani/Analyzing-the-Boston-Airbnb-open-dataset2
