Task 2: Data Cleaning & Exploratory Data Analysis (EDA) – Titanic Dataset

This project is part of my internship at Prodigy Infotech (June 2025) under the Data Science domain.

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📌 Objective:

Perform data cleaning and exploratory data analysis on the Titanic dataset to uncover meaningful patterns, trends, and relationships between variables.

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🛠️ Tools & Libraries Used:

• Python
• Pandas, NumPy
• Matplotlib, Seaborn

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🔎 Key Steps:

• Loaded the Titanic dataset (train.csv)
• Handled missing values (Age, Embarked, dropped Cabin)
• Performed EDA with visualizations:
  • Survival distribution
  • Survival by gender and class
  • Age distribution
  • Correlation heatmap

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✅ Insights:

• Females had a higher survival rate than males
• Passengers in 1st class had better chances of survival
• Most passengers were aged between 20–40

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📁 Dataset Source:

Kaggle – Titanic Dataset

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👩‍💻 Anika
BTech CSE (AI & DS) | Intern at Prodigy Infotech