Welcome to the EDA Public Learning Repository! This repository is dedicated to helping learners understand and perform Exploratory Data Analysis (EDA). It contains various Jupyter notebooks, datasets, and resources to guide you through the process of analyzing and visualizing data.
- data/: Datasets used for analysis.
- notebooks/: Jupyter notebooks for EDA.
- images/: Visualizations generated during the analysis.
- README.md: Project overview and instructions.
- resources/: Additional learning materials and references.
To get started, ensure you have the following installed:
- Python 3.x
- Jupyter Notebook
- Necessary libraries (listed in
requirements.txt)
Clone the repository:
git clone https://github.com/haroontrailblazer/EDA-public-learning.git
cd eda-public-learningInstall the required libraries:
pip install -r requirements.txtNavigate to the notebooks/ directory and open the Jupyter notebook:
jupyter notebook eda_example.ipynbFollow the steps in the notebook to explore the data and generate visualizations.
- Data Loading and Cleaning: Learn how to load and clean datasets.
- Descriptive Statistics: Calculate and interpret summary statistics.
- Data Visualization: Create and understand various plots and charts.
- Feature Engineering: Generate new features from existing data.
- Correlation Analysis: Analyze relationships between variables.
Contributions are welcome! If you have any improvements, additional notebooks, or datasets to share, please fork the repository and submit a pull request.
Join the community of learners and contributors:
- Discussions: Participate in discussions here
- Issues: Report bugs or request features here
For any questions or suggestions, feel free to reach out:
- Email: haroonint144@gmail.com
- GitHub: haroontrailblazer
This project is licensed under the MIT License. See the LICENSE file for details.