Stock Data Prediction using Prophet

A project to forecast stock price movements using Facebook’s Prophet library, based on historical stock data.

Project Structure

• notebooks/ – Jupyter Notebooks for data analysis, model training and evaluation
• requirements.txt – Python libraries needed to run the project
• LICENSE – MIT Licence for this project
• README.md – this file with overview and instructions

Features

• Load historical stock data (e.g. via CSV or APIs)
• Data preprocessing (cleaning, formatting) to make it compatible with Prophet
• Time series forecasting using Prophet for future predictions
• Plotting and visualization of historic vs predicted values
• Quantitative evaluation (e.g. error metrics)
• Jupyter notebooks for interactive exploration

Tools & Libraries

• Python
• pandas
• matplotlib
• yfinance
• fbprophet
• jupyterlab / jupyter notebooks

How to Use

1. Clone the repository:

   git clone https://github.com/nurulashraf/prophet-stock-data-prediction.git
   cd prophet-stock-data-prediction

2. (Optional) Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate       # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Open notebook

   Launch Jupyter:

   jupyter notebook

   or

   jupyter lab

   Then open the notebook in the notebooks/ folder.

License

This project is licensed under the MIT License. See the LICENSE file for full details.