Seattle AirBnb Project

Explore the Seattle AirBnb dataset available on Kaggle: https://www.kaggle.com/datasets/airbnb/seattle

Blog post: https://medium.com/@inrb/how-much-is-seattle-really-worth-it-8996730af9e3

Motivation for the project

The main motivation in choosing the AirBnb dataset to explore pricing and numeric data but also comments and categorical data. As a user of Airbnb it was interesting to see what kind of insights could be discover using their information.

Questions to answer:

1. When is the best time of year to visit Seattle on a budget?

2. Is there any connection between reviews and the price?

3. Whats the most popular neighbourhood in Seattle?

Summary

When is the best time of year to visit Seattle on a budget?

• In terms of price, the most expensive time of year to visit Seattle is the summer in July.

• The cheapest time is in January in Winter

• If you are on a budget then January is best time of year to visit Seattle as the median price of listings is $99 a night

Is there any connection between reviews and the mean price?

• The pearson correlation of between the number of reviews for a listing its average mean price is -0.32, this is relatively low correlation and suggests there is not a strong linear relationship between the quantity of reviews and the average price of a listing

Whats the most popular neighbourhood in Seattle?

• If we assume the number of comments reflects how popular a listing is, then Capitol Hill is the most popular neighbourhood

File Description

SeattleAirBnbProject/archive.zip: Folder containing Listings.csv,Reviews.csv,Calendar.csv

SeattleAirBnbProject/TheSeattleAirbnbProject.ipynb: Notebook containing code and analysis for SeattleAirBnBProject

SeattleAirBnbProject/archive/Listings.csv: Including full descriptions and average review score

SeattleAirBnbProject/archive/Reviews.csv: Including unique id for each reviewer and detailed comments

SeattleAirBnbProject/archive/Calendar.csv: Including listing id and the price and availability for that day

SeattleAirBnbProject/requirements.txt: Including libraries and can be installed with: pip install - requirements.txt

Installation

This code runs with Python version 3.10.12 and requires some libraries, to install these libraries you will need to execute: pip install - requirements.txt

Licensing, Authors, and Acknowledgements

Data Source: https://www.kaggle.com/datasets/airbnb/seattle

Acknowledgements:

Dataset Credit: Murray, C. (2024) Inside Airbnb Data. Available at: https://insideairbnb.com/get-the-data/ (Accessed: 14 March 2025).

License: Creative Commons Attribution 4.0 International License.