1. git clone and then cd into lps

2. Create a virtual environment

   • use Python version 3.11
   • if 3.11 is already in-use python -m venv [name]
   • else virtualenv [name] --python=python3.11

3. Activate the environment

   • Windows: source [name]/Scripts/activate
   • MacOS: source [name]/bin/activate

4. Install requirements

   • pip install -r requirements.txt

Created to tackle the stratascratch "Market Analysis in Dublin" data challenge

We used the given data from searches and contacts of Airbnbs in Dublin to create a random forest machine learning model that can recognize when people are most likely to book a listing.

• Data Management: MySQL database
• Data Manipulation and Analysis: pandas, sklearn
• Data Visualization: plotly

We all had different experience levels in data visualizations and analysis coming into the datathon. Learning how to use different plotting libraries to fulfill our ideas was an uphill battle.

We're proud that we were able to draw conclusions from the data and produce a high-accuracy random forest model.

We learned how to analyze a dataset for use in machine learning and pre-process the data to make the ingest easier. We also learned how to create a story with data to convey all of our research!

Evolving the ML to be able to predict visitors/inquiries based on month of the year