Hotel-Booking-Analysis-using-Python

An end-to-end data analysis project that explores hotel booking patterns,cancellation behavior,seasonal demand, and pricing (ADR) using Python. The project includes data cleaning, exploratory data analysis (EDA), feature engineering,insightful visualization and business recommendation to support revenue optimization and operational decision-making.

📌 Project Objectives

• Analyze hotel booking patterns and customer behavior.
• Identify factors influencing booking cancellations.
• Explore seasonal booking trends and pricing (ADR).
• Compare City Hotels and Resort Hotels across key business metrics.
• Generate actionable business insights and recommendations using data.

🛠️ Tech Stack

• Python
• Pandas
• NumPy
• Matplotlib
• Jupyter Notebook
• Power BI

📊 Key Analyses

• Data Cleaning & Preprocessing
• Feature Engineering
• Exploratory Data Analysis (EDA)
• Booking Pattern Analysis
• Cancellation Analysis
• Average Daily Rate (ADR) Analysis
• Seasonal Trend Analysis
• Business Insights & Recommendations

🎯 Business Impact

This analysis helps hotel managers and stakeholders:

• Understand customer booking behavior.
• Identify major causes of booking cancellations.
• Optimize pricing strategies based on seasonal demand.
• Reduce dependence on third-party booking channels.
• Improve occupancy, operational planning, and overall revenue.