🚀 Project Highlights: ➡️ Data Cleaning: Rectified missing values and outliers. ➡️ Data Transformation: Introduced new columns like occupancy%. ➡️ Insights Generation: Explored crucial questions such as average occupancy rates, weekday versus weekend occupancy, city-wise revenue, monthly revenue trends, and platform-specific revenue analysis.
🔥 Skills Developed: ➡️ Proficiency in Python: Expertise in data analysis, cleaning, transformation, and visualization. ➡️ Data Visualization: Utilized Matplotlib to craft engaging charts and graphs. ➡️ Pandas Basics: Mastered techniques for data manipulation such as groupby, concat, merge, handling NA values, and CSV file processing.
💡 Key Findings: ➡️ Revenue Leaders: Mumbai emerged as the top earner with 669M INR; May recorded the highest revenue at 581.93M INR. ➡️ Customer Preferences: Presidential rooms received the highest rating of 3.69; Delhi showcased an average rating of 3.78. ➡️ Occupancy Champion: Delhi not only received impressive ratings but also boasted the highest occupancy rate at 62.47%.
🚀 Recommendations: ➡️ Mumbai Momentum: Invest in targeted marketing initiatives to further amplify revenue. ➡️ Premium Enhancement: Elevate the premium room experience to improve ratings and potentially increase revenue. ➡️ Optimizing Delhi Stays: Despite high ratings, explore strategies to maximize room bookings in Delhi. ➡️ Weekend Promotions: Leverage the weekend rush by implementing targeted marketing campaigns on Fridays and Saturdays.