Predicting AirBnB prices

Directory Structure

.
├── README.md
├── project_predicting_AirBnB_prices.md (the write-up of the project)
├── Notebook.ipynb (the Jupyter notebook containing the code)
├── Data (containing the AirBnB listings data in csv format)
├── Figures (contains figures used in the write-up)
├── Performances (contains figures used in the write-up)

Requirements

Python 3.6
scikit-learn
Pandas
Numpy
seaborn
scipy
statsmodels

Instructions to re-run the code

If you would like to run the notebook, first download the csv file (containing Airbnb listings.csv) and then set the variable "CSV_local_address" in the second cell of the notebook to the local addrress of the downloaded file.