Mustapha-Dafa/Sentiment-Analysis-of-Tourists-and-Forecasting-of-Tourism-Indicators-in-Morocco

# PFA Project — Tourism Analysis (Ministry of Finance Internship) Summary ------- This project collects, cleans, and analyzes tourism-related data from Booking, Google Maps, Tripadvisor and Google Trends. It trains and evaluates forecasting and ML models (SARIMA, SARIMAX, Random Forest, Ridge, XGBoost) and provides a Streamlit dashboard for visualization and predictions. Repository structure -------------------- - src/ - Booking/ # Booking scrapers and data - Google Maps/ # Google Maps scrapers and data - Google Trend/ # Pytrends scripts, raw JSON/CSV timelines - Tripadvisor/ # Tripadvisor scrapers and data - notebooks/ - chose_keyword.ipynb - models/ # RF, Ridge, SARIMA, SARIMAX, XGBoost notebooks - data/ - reviews/ # raw & classified reviews - tourism/ # KPI, nights per destination, TES features, etc. - images/ or assets/images/ # images used in reports or dashboard - Requirements.txt # pinned dependencies - README.md # this file Key dependencies ---------------- See Requirements.txt for pinned versions. Primary packages used: - Python 3.10 - pandas, numpy, scipy - scikit-learn, xgboost, statsmodels - matplotlib, seaborn, plotly - streamlit, streamlit-option-menu - requests, beautifulsoup4, lxml, selenium, pytrends - wordcloud, tqdm, joblib,openpyxl