Objective: Utilizing python with machine learning (ML) to analyze views of yacht and boat listings on an online seller platform.
Goal: As a data analyst for a yacht and boat sales website, I've been tasked by the marketing team to analyze recent pricing and listing views data for their weekly newsletter. We're aiming to help sellers boost views and stay informed on market trends.
- What are the characteristics of the most viewed listings in the past week?
- Do the priciest boats attract the most attention?
- Are there common features among the top-viewed boats?
- Utilize open-source data from Kaggle, additional geographical data from geojson.
Boat Sales Data:
- Utilizing the latest versions of MS Excel, Anaconda, Jupyter Notebook, and Python.
Data limitations/challenges:
- There were approx. 5% NAN values in entire dataset but scattered; left as is (accounting for outliers) due to no missing view counts.
- No confirmation of metrics used in measurements
- No purchase data
- No measurement for website views by time of day/month/year.