This interactive dashboard allows users to explore the famous Titanic dataset, analyzing how different factors influenced passenger survival rates during the disaster.
Data Exploration View the initial dataset structure
Apply dynamic filtering based on age and fare thresholds
Examine filtered data in tabular format
Interactive Visualizations Scatter Plot: Visualize the relationship between age, fare, and survival
Dashboard: View survival distribution and fare distribution by passenger class
3D Visualization: Explore the relationship between age, fare, family size, and survival
Sankey Diagram: Track passenger flow through different categories to survival outcomes
Correlation Heatmap: Analyze relationships between various features and survival
User Controls Age and fare threshold sliders
Gender and passenger class filters
Point size and opacity controls for 3D visualization
Correlation method selection
Sorting options for correlation analysis
The dashboard reveals several patterns in the Titanic disaster:
Women had significantly higher survival rates than men
Higher class passengers (1st class) were more likely to survive
Family size interacted with age and fare to influence survival probability
The Sankey diagram shows common paths to survival, such as Class 1 → Female → Adult → High Fare → Survived
Age and fare threshold sliders
Gender and passenger class filters
Point size and opacity controls for 3D visualization
Correlation method selection
Sorting options for correlation analysis
- Configure your data connections in
preswald.toml - Add sensitive information (passwords, API keys) to
secrets.toml - Run your app with
preswald run