CodeAlpha Internship - Task 2: Exploratory Data Analysis (Titanic Dataset)

📌 Project Overview

This repository contains my submission for Task 2: Exploratory Data Analysis (EDA) as part of the CodeAlpha Data Analytics Internship.
The goal of this task is to explore the Titanic dataset, identify patterns, detect anomalies, and generate insights using statistical and visualization techniques.

🛠️ Tools & Libraries

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn

📂 Files in Repository

• Task2_Titanic_EDA.ipynb → Jupyter Notebook with code and explanations
• titanic.csv → Dataset used for analysis

🚀 Steps Performed

1. Loaded and inspected the Titanic dataset.
2. Explored data structure, variables, and data types.
3. Handled missing values and cleaned the dataset.
4. Analyzed survival rates by gender, passenger class, and age groups.
5. Visualized trends using bar charts, histograms, and heatmaps.
6. Tested hypotheses and validated assumptions with statistics.

🎯 Key Insights

• Female passengers had a higher survival rate compared to males.
• Passengers in higher classes (1st class) had better chances of survival.
• Younger passengers showed higher survival probability compared to older ones.