Advanced Hotel Booking Data Analysis
Budget: ₹600 – ₹1,500 INR
This project focuses on analyzing hotel booking data to uncover customer behavior patterns, booking trends, and cancellation insights. Using Python-based data analysis and visualization tools, the project delivers actionable findings that can help hotels improve revenue management, reduce cancellations, and enhance customer satisfaction.
The analysis involved:
Cleaning and preparing raw booking data by handling missing values, outliers, and incorrect data types.
Performing exploratory data analysis (EDA) to identify booking distribution, seasonal trends, and cancellation rates.
Visualizing key metrics such as ADR (Average Daily Rate), room type demand, and booking lead time using Matplotlib and Seaborn.
Highlighting critical insights, such as 37% of bookings being canceled and significant differences between resort and city hotels.
The analysis involved:
Cleaning and preparing raw booking data by handling missing values, outliers, and incorrect data types.
Performing exploratory data analysis (EDA) to identify booking distribution, seasonal trends, and cancellation rates.
Visualizing key metrics such as ADR (Average Daily Rate), room type demand, and booking lead time using Matplotlib and Seaborn.
Highlighting critical insights, such as 37% of bookings being canceled and significant differences between resort and city hotels.
Related categories:
Python
Data Processing
Statistics
Data Mining
Big Data Sales
Data Visualization
Data Analysis
Data Management