Context
This dataset contains 49 cleaned customer reviews for a local dental clinic in Newport News, VA, USA. The data was scraped from a single Google My Business (GMB) listing in October 2025 using Apify.

This dataset was prepared as the first step in a portfolio project to demonstrate Aspect-Based Sentiment Analysis (ABSA) for local SEO and reputation management.

Content

The file cleaned_gmb_reviews.csv contains three columns:

• clinic_name: (text) The name of the GMB listing.
• rating: (integer) The star rating given by the user (1-5).
• review_text: (text) The full text of the review.

Data Cleaning Process

The raw data (100 rows) was programmatically cleaned using Python and the pandas library to:

1. Select only the essential columns (title, stars, text).
2. Rename columns for clarity (e.g., stars to rating).
3. Extract the clean integer (e.g., 5) from the text-based rating (e.g., "5 stars").
4. Remove 51 rows that had no written review text, as they are not usable for text analysis.

Inspiration

This dataset is ideal for answering several key business questions:

• What is the overall sentiment (Positive, Negative) of the reviews?
• What specific topics (e.g., "pricing", "wait time", "Dr. Ali") do customers mention most often?
• What are the primary pain points for this clinic's customers?