hotel booing data set using python

Purpose: To explore booking trends and uncover insights to support business decisions in the hospitality sector

Key Tasks Performed:

Data Cleaning: Removed duplicates, handled missing values, corrected data types

Data Transformation: Merged datasets, created new features (e.g., length of stay, cancellation rate)

Exploratory Analysis:

Booking patterns by month, country, and hotel type

Cancellation rates and their correlation with lead time and booking source

Distribution of guests by market segment and room type