reviews-analyzer

Customer Review Insights

A Python tool that reads customer reviews from a CSV file, scores each review’s sentiment using TextBlob, and prints a summary of what customers feel.

Note: This is a recreated version of my coursework project. The original files were lost with my old laptop, so I rebuilt it from scratch. reviews.csv contains sample reviews written for demonstration.

What it does

• Reads reviews from reviews.csv (columns: review_id, review_text)
• Calculates polarity (-1 negative to +1 positive) and subjectivity (0 to 1) for each review
• Labels each review as Positive, Neutral or Negative
• Prints counts, percentages, average polarity, the most positive and most negative review, and common words in positive/negative reviews
• Saves all scores to results.csv

How to run

pip install -r requirements.txt
python analyze_reviews.py

To use your own data, create a CSV with the same two columns and run:

python analyze_reviews.py my_reviews.csv

How the labels work

| Polarity | Label | |—|—| | above 0.1 | Positive | | -0.1 to 0.1 | Neutral | | below -0.1 | Negative |

Tech

Python 3.9+, TextBlob, csv, collections

Ideas to extend

• Add a chart of sentiment counts with matplotlib
• Analyse reviews by product or date
• Compare TextBlob with another sentiment tool