Titanic Data Analysis

Jupyter Notebook

A project exploring the Titanic disaster dataset, investigating various factors that influenced passenger survival rates. Through descriptive statistics, data visualizations, and correlation analysis, it provides valuable insights into the demographics and conditions surrounding the tragic event.

Project Summary:

In this project, we conducted an exploratory data analysis (EDA) on the Titanic disaster dataset to uncover valuable insights about the factors influencing passenger survival rates. The primary objective was to understand the dynamics of this historical tragedy and gain deeper knowledge of the passengers' demographics and conditions.

We started by describing the variables in the dataset, such as age and passenger class. After cleaning the data and handling missing values, we delved into visualizations to better grasp the data's distribution and relationships between different features. Through various plots and charts, we identified significant patterns, correlations, and trends.

Our analysis revealed that certain factors, such as passenger class and age, played crucial roles in determining survival rates. These findings offered important insights into the events surrounding the Titanic disaster and highlighted the disparities in survival rates across different groups.

Overall, this EDA provided a comprehensive understanding of the dataset and enriched our knowledge of the Titanic disaster, shedding light on the human stories and dynamics that unfolded during that tragic event.

Click the Jupyter Notebook link located near the top of the page to view all of the code and data visualisations.