https://github.com/manish-jsx/dataapps_using_streamlit
Deploying Machine Learning Trained Models at Work
https://github.com/manish-jsx/dataapps_using_streamlit
matplotlib newsapi newsapi-python pandas streamlit-dashboard streamlit-webapp yfinance-api
Last synced: 17 days ago
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Deploying Machine Learning Trained Models at Work
- Host: GitHub
- URL: https://github.com/manish-jsx/dataapps_using_streamlit
- Owner: manish-jsx
- Created: 2024-05-21T16:17:32.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-21T16:46:12.000Z (about 2 years ago)
- Last Synced: 2025-07-07T21:11:12.314Z (11 months ago)
- Topics: matplotlib, newsapi, newsapi-python, pandas, streamlit-dashboard, streamlit-webapp, yfinance-api
- Language: Python
- Homepage: https://stock-price-yfinance.streamlit.app/
- Size: 111 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Simple Stock Price App
This is a simple web application to fetch and display historical stock prices using Streamlit and Yahoo Finance.
## Screenshots
## Features
- User can input a stock ticker symbol.
- Displays historical closing prices of the stock.
- Shows basic statistics of the stock data.
## Installation
1. Clone the repository or download the source code.
2. Navigate to the project directory.
```bash
cd simple-stock-price-app
```
3. Install the required dependencies.
```bash
pip install -r requirements.txt
```
## Running the App
To run the Streamlit app, use the following command:
```bash
streamlit run streamlit_app.py
```
This will start a local server and open the app in your default web browser.
## File Structure
- `streamlit_app.py`: Main Streamlit application script.
- `requirements.txt`: List of dependencies.
- `.streamlit/config.toml`: Configuration file for Streamlit.
- `README.md`: Project overview and instructions.
## Usage
1. Open the app in your web browser.
2. Enter a stock ticker symbol (e.g., `AAPL` for Apple Inc.).
3. View the historical closing prices and basic statistics.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request.
## License
This project is licensed under the MIT License.