Project Overview
I automated the process of data acquisition from Goodreads using Selenium, successfully building a clean dataset of over 4,000 book records. This data included detailed ratings, genre classifications, and author metadata.
Following the data extraction, I performed an in-depth statistical analysis with NumPy and Pandas to uncover critical trends, such as top-performing genres and the correlation between book scores and user ratings. Finally, I developed compelling data visualizations using Matplotlib to present these findings.
Data Insights
A sample chart showing the correlation between book scores and user ratings.
