This project analyzes data from Airbnb listings in New York City. It includes data visualization, sentiment analysis, recommendation systems, and predictive modeling.

• Data visualization using Matplotlib, Seaborn, and Folium
• Sentiment analysis using NLTK and VADER
• Recommendation systems using Surprise and SVD
• Predictive modeling using Scikit-learn and Linear Regression
• Random Forest Regressor for comparison

• Python 3.6+
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Folium
• NLTK
• Surprise
• Scikit-learn

1. Clone the repository: git clone https://github.com/your-username/airbnb-data-analysis.git
2. Install the requirements: pip install -r requirements.txt
3. Run the analysis: python analysis.py

1. Open the analysis.py file to view the code.
2. Run the code to generate the visualizations and analysis.
3. View the results in the visualizations folder.

pandas numpy matplotlib seaborn folium nltk surprise scikit-learn