https://github.com/swish78/home.llc
https://github.com/swish78/home.llc
Last synced: over 1 year ago
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- Host: GitHub
- URL: https://github.com/swish78/home.llc
- Owner: Swish78
- License: mit
- Created: 2024-07-25T05:59:24.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-25T06:10:17.000Z (almost 2 years ago)
- Last Synced: 2024-07-25T07:23:14.326Z (almost 2 years ago)
- Language: Jupyter Notebook
- Size: 11.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# US Home Prices Analysis
This repository contains the analysis of key factors influencing US home prices over the last 20 years. The S&P Case-Schiller Home Price Index is used as a proxy for home prices. The project involves Exploratory Data Analysis (EDA), modeling, and results documentation.
## Repository Structure
- **`EDA.ipynb`**: Jupyter notebook for Exploratory Data Analysis. This notebook includes data cleaning, visualization, and preliminary insights.
- **`Modeling.ipynb`**: Jupyter notebook for building and evaluating machine learning models to understand the impact of various factors on home prices.
- **`house.py`**: Python script containing data processing code used in the analysis.
- **`requirements.txt`**: List of required Python packages for running the notebooks and scripts.
- **`README.md`**: Documentation file providing an overview of the project.
- **`LICENSE`**: License file specifying the terms of use for this repository.
- **`Summary.pdf`**: Detailed report summarizing the findings and insights from the analysis.
- **`eda.pdf`**: PDF version of the Exploratory Data Analysis notebook.
## Getting Started
To run the notebooks and scripts, follow these steps:
1. **Clone the Repository:**
```bash
git clone https://github.com/yourusername/Home.LLC.git
```
2. **Navigate to the Repository:**
```bash
cd Home.LLC
```
3. **Install Dependencies:**
```bash
pip install -r requirements.txt
```
4. **Run the Notebooks:**
Open `EDA.ipynb` and `Modeling.ipynb` in Jupyter Notebook or JupyterLab and execute the cells to reproduce the analysis and results.
## Data Sources
- **S&P Case-Schiller Home Price Index**: [Link to Data](https://fred.stlouisfed.org/series/CSUSHPISA)
- **Additional Data**: Data sources for key factors influencing home prices are included in the notebooks.
## License
This project is licensed under the [MIT License](LICENSE).
## Acknowledgments
- [FRED - Federal Reserve Economic Data](https://fred.stlouisfed.org/) for providing the data.
## Contact
For questions or further information, please contact [Your Name](mailto:swayam.work25@gmail.com).