Welcome to the Titanic Dataset Analysis repository! This project leverages the Titanic dataset from Kaggle to explore and visualize various factors that influenced passenger survival rates during the tragic sinking of the RMS Titanic.
This repository contains a comprehensive analysis of the Titanic dataset, including visualizations such as bar graphs, pie charts, and scatter plots. These visualizations help to uncover insights into how different variables like passenger class, gender, fare, age, and embarkation point affected survival outcomes.
The dataset used in this analysis is sourced from the Kaggle Titanic competition. It includes detailed information about the passengers, such as:
- PassengerId: Unique identifier for each passenger
- Survived: Survival status (0 = No, 1 = Yes)
- Pclass: Passenger class (1 = 1st, 2 = 2nd, 3 = 3rd)
- Name: Name of the passenger
- Sex: Gender of the passenger
- Age: Age of the passenger
- SibSp: Number of siblings/spouses aboard the Titanic
- Parch: Number of parents/children aboard the Titanic
- Ticket: Ticket number
- Fare: Passenger fare
- Cabin: Cabin number
- Embarked: Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)
The analysis includes the following visualizations:
- Survival Rate by Class: Examines how passenger class influenced survival rates.
- Survival Rate by Gender: Analyzes the impact of gender on survival.
- Fare Distribution: Shows the distribution of fares paid by passengers.
- Age Distribution: Visualizes the age distribution of passengers.
- Embarkation Points: Highlights the survival rates based on the port of embarkation.
Tools Used The analysis was conducted using Power BI for creating interactive and insightful data visualizations. Additionally, Google Colab was utilized for performing the data analysis in Python. You can view the Colab notebook here.