Airbnb's Pot of Gold

Inspiration

We were inspired by a firm desire to create a project with a clear, undeniable positive societal impact. We chose to work on this project because we believed that we could create a market analysis that can improve the experience for visitors of Dublin, Ireland, as well as those facing housing problems in the region.

What it does

In our project, we first analyze the data provided to us, which consists of search queries for Airbnbs in Dublin, Ireland, and successful booking confirmations. We then used our data analyses to predict whether a customer will make an Airbnb booking based on a set of given data regarding the customer's booking process.

How we built it

We started off by making a simple graph of the search frequencies over the 2-week period described in the data provided to us. From there, we chose interesting, relevant variables to perform data analyses on and visualized that data. We performed these visualizations in Python. Then, we used the data to train a machine learning model to predict whether a customer will make an Airbnb booking based on any number of these variables related to the customer's booking process.

Challenges we ran into

We faced difficulty in merging the datasets. We were provided with two tables, which we needed to merge into a single table to perform certain statistical analyses. This data manipulation proved to be difficult to perform while maintaining the accuracy of the data.

Accomplishments that we're proud of

We are proud of the performance of our machine learning model, which has an MAE of 0.18, indicating a high level of accuracy at 82%.

What we learned

Over the course of this project, we learned a lot about the process of data manipulation, extrapolating data, and how to maintain the quality of data while manipulating it, which can be difficult.

What's next for Dublin Airbnb Market Analysis

In future iterations of the project, we would improve the data cleaning process and organize it better, including finding more patterns to further understand trends.