Moggycool/Customer-Experience-Analytics--Week2-Challange

This week’s challenge centers on analyzing customer satisfaction with mobile banking apps by collecting and processing user reviews from the Google Play Store for three Ethiopian banks: Commercial Bank of Ethiopia (CBE); Bank of Abyssinia (BOA); Dashen Bank # Customer-Experience-Analytics--Week2-Challange This week’s challenge centers on analyzing customer satisfaction with mobile banking apps by collecting and processing user reviews from the Google Play Store for three Ethiopian banks: Commercial Bank of Ethiopia (CBE); Bank of Abyssinia (BOA); Dashen Bank --- ## Project Structure ```Customer-Experience-Analytics--Week2-Challange ├─ .env ├─ data │ ├─ preprocessed │ │ └─ google_play_processed_reviews.csv │ ├─ raw │ │ ├─ google_play_app_info.csv │ │ └─ google_play_raw_reviews.csv │ └─ README.md ├─ notebooks │ ├─ preprocessing_eda.ipynb │ └─ scraping_eda.ipynb ├─ README.md ├─ requirements.txt ├─ scripts ├─ src │ ├─ config.py │ ├─ preprocessing.py │ ├─ scraping.py │ ├─ __init__.py │ └─ __pycache__ │ ├─ config.cpython-313.pyc │ ├─ preprocessing.cpython-313.pyc │ ├─ scraping.cpython-313.pyc │ └─ __init__.cpython-313.pyc └─ workflows ├─ CI.yml └─ unittest.yml ``` ` --- ## Features ### 1. Git Setup - GitHub repository initialized. - `.gitignore` included to avoid tracking unnecessary files. - `requirements.txt` included for reproducible environment. - All work done on the `task-1` branch. - Frequent commits with meaningful messages to capture logical chunks of work. ### 2. Web Scraping - Uses `google-play-scraper` to collect reviews from Google Play. - Data collected for three Ethiopian banks. - Each review includes: - `review` text - `rating` (1–5 stars) - `date` of review - `app` name - `bank_code` - Targeted a minimum of **400+ reviews per bank**, totaling over 1,200 reviews. ### 3. Preprocessing - Remove duplicate reviews. - Handle missing or incomplete data. - Normalize dates to `YYYY-MM-DD` format. - Save preprocessed data to CSV with the following columns: review, rating, date, bank, source --- ## 4. Visualizations & Analysis ### a) Ratings Distribution - Shows the count of each star rating (1–5) across all reviews. - Helps identify overall customer satisfaction. ### b) Reviews …