Capstone Project 2 |Almabetter Project | Hotel Booking Analysis |

Welcome to my Hotel Booking Analysis project! In this video, I'll walk you through an in-depth analysis of hotel bookings using Python, pandas, and various data visualization techniques. Whether you're a data enthusiast, a student, or a professional looking to enhance your data analysis skills, this project will provide valuable insights into real-world data handling and visualization.

What You'll Learn:

Data Cleaning: Handling missing values and preparing the dataset for analysis.
Exploratory Data Analysis (EDA): Extracting meaningful insights from the data.
Data Visualization: Using libraries like matplotlib and seaborn to create informative visualizations.
Statistical Analysis: Understanding booking patterns, customer behavior, and trends.
Python Programming: Practical implementation of Python code to analyze and visualize data.
Project Overview:

Introduction:
Overview of the project and dataset.
Goals and objectives of the analysis.

Data Preparation:
Loading the dataset.
Handling missing values.
Data transformation and feature engineering.

Exploratory Data Analysis (EDA):
Analyzing booking trends over time.
Understanding customer demographics.
Examining booking cancellation rates.

Data Visualization:
Creating visualizations to represent data insights.
Heatmaps, bar charts, pie charts, and more.

Statistical Insights:
Identifying key factors influencing bookings.
Seasonal trends and peak booking periods.
Customer behavior analysis (single, couple, family bookings).

Conclusion:
Summary of findings.
Future work and potential improvements.

Github Link - https://github.com/ShivamGuptaaaa/Cap...

Linkdin Link -   / shivamguptaaaa