PRODIGY_DS_02
Titanic Dataset Exploration and Cleaning
Overview
This project focuses on performing data cleaning and exploratory data analysis (EDA) on the Titanic dataset obtained from Kaggle. The primary goal is to delve into the dataset, identify patterns, trends, and relationships between variables, and subsequently clean the data to facilitate further analysis.
Dataset
The Titanic dataset used in this project is sourced from Kaggle and can be accessed here. It consists of various features related to passengers aboard the Titanic, including information such as age, sex, ticket class, and survival status.
Getting Started
To run the analysis and explore the dataset, follow these steps:
Clone the Repository:
git clone https://github.com/Aabidnabi/PRODIGY_DS_02.git
cd titanic-dataset-exploration
Install Dependencies:
pip install -r requirements.txt
Download the Dataset:
Visit Kaggle Titanic Dataset and download the dataset. Place the downloaded CSV file in the project directory.
Run the Analysis:
python explore_and_clean.py Analysis Steps
Data Cleaning:
Handle missing values. Address outliers. Standardize and format data.
Exploratory Data Analysis (EDA):
Visualize the distribution of variables. Explore relationships between features. Identify patterns and trends. Analyze survival rates based on different factors.
Results and Insights:
Summarize key findings. Present visualizations that highlight important trends. Draw conclusions about the dataset. Contributing If you'd like to contribute to this project, feel free to open an issue or submit a pull request. Contributions are welcome!
License
This project is licensed under the MIT License.
Acknowledgments
Special thanks to Kaggle for providing the Titanic dataset and the open-source community for valuable insights.
Happy analyzing!