🚢 Titanic Data Visualization App

An interactive data visualization web app built with Python, Pandas, Seaborn, Matplotlib, and Streamlit. It provides insights into passenger demographics and survival patterns from the Titanic dataset.

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📌 Project Overview

This project visualizes the Titanic dataset from Kaggle using interactive charts and graphs. It aims to help users understand how various factors like gender, passenger class, and age affected survival during the Titanic disaster.

🔍 Features:

• View raw Titanic dataset
• Countplot of total survivors
• Survival comparison by gender
• Age distribution of passengers
• Survival based on ticket class

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🧠 Logic and Tools Used

📊 Visualization Logic:

1. Survival Count – Visualizes how many survived vs not.
2. Survival by Gender – Gender-wise survival comparison.
3. Age Distribution – Histogram and KDE plot of passenger ages.
4. Survival by Class – Shows how class (1st/2nd/3rd) affected survival.

🛠️ Tools:

• Pandas: For data cleaning and loading CSV.
• Matplotlib & Seaborn: For visualizations.
• Streamlit: To build interactive web UI.

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📁 Dataset

Download the dataset from Kaggle Titanic Competition.
Place the train.csv file in the root directory of this project.

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🚀 How to Run the Project

Follow the steps below to clone and run the project locally:

1️⃣ Clone the repository:

git clone https://github.com/yourusername/titanic-visualization-app.git
cd titanic-visualization-app
streamlit run app.py