My Medium post on this project is here. (https://medium.com/@kitozuka/want-to-run-a-vacation-rental-understanding-airbnb-rent-prices-in-seattle-d64dc15b8e28)
- folium: I used folium package to create interactive maps that contain marker plots and choropleth plots. Other than this, I used libraries from Anaconda the distribution.
To understand the factors of determining rent price on Airbnb listings, I use "Kaggle Seattle Airbnb Open Data"(https://www.kaggle.com/airbnb/seattle), which includes listings data in 2016. I will look into this by exploring the following three sub-questions:
- When are the busier days or seasons in Seattle? What are the average prices then?
- What is the number of listings and the median price over night in the neighborhood?
- Which factors have a strong correlation with the price of listings?
Those files below are the major ones for running the project.
- Seattle AirBnB_2.ipynb: This ipynb file is the main Jupyter notebook I made analysis. This contains codes for geospatial maps and some statistical models.
- ScatterListings.html: This html file includes geospatial scatter plot of Airbnb listings, colored by rent prices with pupup lables.
- med_price.html: This html file includes the median rent prices with popup labels by neighborhood in Seattle
Although I created some interactive maps using folium, the file sizes are too to show on github. To view the results fully, you can downloead the html files (ScatterListings.html, med_price.html). I also run some machine learning models to predict rent prices. I mainly tried Random Forest + GridsearchCv to find the best model, but I did not try ensemble models with multiple algorithms. However, I got R-squared of around 62%.
I wrote this blog as a project for Udacity Data Scientist Nanodegree Program. I appreciate Udacity to give me this opportunity to hone my skill in analyzing and presenting real-world dataset. I also want to thank peer learners, especially Adnan Shaikh for their medium post (https://medium.com/@kaddu4u/understanding-the-rental-prices-of-airbnb-in-seattle-29a0427889e9) that helped me get a sense of the project.