Hotel Booking Cancellation Analysis

Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn

Explored and cleaned a comprehensive hotel booking dataset to

identify key factors influencing guest cancellations.

Performed Exploratory Data Analysis (EDA) to uncover trends related

to lead time, deposit types, and customer segments.

Engineered new features to capture complex behavioral patterns,

such as calculating the total stay duration and categorizing lead

times to enhance predictive power.

Applied Principal Component Analysis (PCA) to reduce dataset

dimensionality while retaining maximum variance, optimizing

computational efficiency for subsequent modeling.

Visualized booking patterns and cancellation rates across different

hotel types (City vs. Resort hotels).

Identified critical insights to help hotel management reduce revenue

loss by predicting high-risk bookings.