A clean dataset of 49 Google Maps reviews for a local dental clinic.
Dataset Description
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:
- Select only the essential columns (
title,stars,text). - Rename columns for clarity (e.g.,
starstorating). - Extract the clean integer (e.g., 5) from the text-based rating (e.g., "5 stars").
- 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?
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