This project explores the Titanic dataset to uncover patterns and insights about passenger survival.
The analysis focuses on understanding the factors that influenced survival during the Titanic disaster. The workflow includes:
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Data Loading & Exploration
Importing the dataset and reviewing its structure and key features. -
Data Cleaning
Handling missing values and inconsistencies for accurate analysis. -
Feature Transformation
Converting categorical variables (e.g., gender, embarkation) into numeric formats. -
Statistical Insights
Generating summary statistics and grouping by categories such as gender and passenger class. -
Data Visualization
Using Python libraries to create bar plots, heatmaps, and other visualizations that highlight patterns and correlations. -
Key Findings
Highlighting survival rates across different passenger groups.