Titanic Dataset Analysis (Work in Progress)

This project is focused on analyzing the Titanic dataset using Python, with the goal of predicting passenger survival. https://www.kaggle.com/datasets/yasserh/titanic-dataset

Project Overview

The analysis includes:

• Data preprocessing and cleaning
• Exploratory Data Analysis (EDA)
• Feature engineering
• Machine learning model preparation

Dependencies

• Python 3.x
• pandas
• numpy
• matplotlib
• seaborn
• scikit-learn

Dataset

The project uses the famous Titanic dataset, which includes the following features:

Feature	Description
Survival	Survival (0 = No, 1 = Yes)
Pclass	Ticket class (1 = 1st, 2 = 2nd, 3 = 3rd)
Sex	Gender
Age	Age in years
SibSp	Number of siblings/spouses aboard
Parch	Number of parents/children aboard
Fare	Passenger fare
Embarked	Port of embarkation (C, Q, S)

Current Progress

• Initial data loading and inspection
• Basic data cleaning (removing unnecessary columns)
• Feature encoding for categorical variables
• Correlation analysis using heatmap
• Data splitting into training and test sets
• Feature engineering
• Model selection and training
• Model evaluation
• Predictions on test data

Project Structure

├── data/
│ ├── train.csv
│ └── test.csv
└── sample.ipynb

Work in Progress

This project is currently under development. Future updates will include:

• Complete feature engineering
• Implementation of various machine learning models
• Model performance comparison
• Final predictions and analysis

Getting Started

1. Clone the repository
2. Ensure you have all required dependencies installed
3. Run the Jupyter notebook to see the analysis

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⚠️ Note: This is a work in progress, and updates will be made I dont know when.