Titanic — Passenger Survival Analysis

Overview

Titanic — Passenger Survival Analysis is a data-driven project that examines passenger characteristics and survival outcomes from the Titanic dataset. The analysis explores how demographic, travel, and family-related factors relate to survival patterns, using data preparation, exploratory analysis, and visualization to communicate meaningful findings.

Key Features

• Passenger Profile Analysis: Examines 891 passenger records across age, gender, passenger class, fare, and family-related characteristics
• Survival Analysis: Explores survival patterns across key passenger demographics and travel characteristics
• Data Preparation: Cleans and transforms the Titanic dataset to prepare it for accurate and consistent analysis
• Comparative Analysis: Compares survival outcomes across passenger classes, genders, age groups, and family sizes
• Data Visualization: Presents passenger and survival patterns through clear visualizations that make key findings easier to interpret

Analysis Approach

The project follows a structured exploratory data analysis workflow covering data inspection, cleaning, transformation, descriptive analysis, and visualization. Passenger characteristics are analyzed individually and comparatively to identify patterns associated with survival outcomes.

Key Insights

The analysis identified an overall survival rate of approximately 38.4% across the 891 passengers, with an average passenger age of approximately 30 years. Examining survival across demographic and travel characteristics provides a clearer understanding of how passenger profiles varied across the dataset.

Technologies

Python, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook, Data Cleaning, Exploratory Data Analysis, Data Visualization.