Brent Oil Prices Analysis

Overview

This project analyzes Brent crude oil prices using various data science techniques, including data preprocessing, exploratory data analysis (EDA), time series modeling, and advanced predictive modeling. The project also includes a Flask and React dashboard for interactive analysis.

Project Structure

Directories

• data/: Contains raw and processed datasets used in the analysis.

  • raw/: Raw data files (e.g., historical oil prices).
  • processed/: Processed data ready for analysis.
  • external/: External data sources (e.g., economic indicators).
  • README.md: Describes data files and sources.

• notebooks/: Jupyter notebooks for various stages of analysis.

  • 01-data-preprocessing.ipynb: Data cleaning and preprocessing steps.
  • 02-exploratory-data-analysis.ipynb: EDA with visualizations.
  • 03-time-series-analysis.ipynb: Time series modeling (ARIMA, GARCH).
  • 04-advanced-models.ipynb: Advanced models (VAR, LSTM).
  • README.md: Overview of notebooks.

• src/: Source code for data preprocessing, feature engineering, and modeling.

  • data_preprocessing.py: Preprocess data and save processed data.
  • feature_engineering.py: Add features to the processed data.
  • model_building.py: Model building functions (ARIMA, GARCH, LSTM).
  • evaluation.py: Evaluate models with metrics like RMSE, MAE.
  • README.md: Overview of scripts.

• models/: Saved models for further use or evaluation.

  • baseline/: Baseline models (e.g., ARIMA, GARCH).
  • advanced/: Advanced models (e.g., LSTM, VAR).
  • README.md: Model details and evaluation results.

• dashboard/: Flask and React dashboard for interactive analysis.

  • backend/: Flask API backend.
    • app.py: Flask API for data and models.
    • config.py: Configuration settings for backend.
    • routes/: API route definitions.
    • README.md: Backend overview.
  • frontend/: React frontend.
    • src/: Source folder for React app.
    • public/: Public assets and static files.
    • components/: React components (charts, filters).
    • README.md: Frontend overview.
  • README.md: Dashboard overview.

• reports/: Documentation, reports, and presentation materials.

  • research-papers/: Relevant journal articles and references.
  • presentation/: Slide decks and presentation files.
  • analysis-summary.md: Summary of analysis and insights.
  • README.md: Documentation overview.

• requirements.txt: Python package requirements.

Installation

To set up the project, clone this repository and install the necessary dependencies:

git clone https://github.com/DegaregeN/Time-series-data-modeling-.git
cd brent-oil-prices-analysis
pip install -r requirements.txt