Metadata-Version: 2.4
Name: enerlytics
Version: 0.1.1
Summary: Renewable Energy Insights Dashboard — data analysis project exploring how U.S. renewable energy production has evolved from 1973 to 2024.
Author-email: Huseyin Kucukogul <huseyinkucukogulcontact@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Huseyin
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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Project-URL: Homepage, https://github.com/Kucukogul/enerlytics
Project-URL: Repository, https://github.com/Kucukogul/enerlytics
Keywords: energy,renewable energy,data science,dashboard,analytics
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: streamlit
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: prophet
Requires-Dist: scikit-learn
Requires-Dist: statsmodels
Dynamic: license-file

# Renewable Energy Insights Dashboard

Data analysis project exploring how U.S. renewable energy production — solar, wind, hydroelectric, geothermal, and biomass — has evolved from 1973 to 2024.

Cleans and aggregates EIA consumption data, visualizes trends by source and sector, and forecasts future consumption with Holt-Winters and Prophet.

---

## Setup

```bash
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
```

---

## Quick Start

```bash
# Run the dashboard
streamlit run app/dashboard.py
```

Dashboard → `http://localhost:8501` · Live demo → https://powerthefuture.streamlit.app/

---

## Structure

```
enerlytics/
├── app/
│   └── dashboard.py                         # Streamlit dashboard
├── notebook/
│   ├── 01_data_cleaning.ipynb               # Data loading & preprocessing
│   ├── 02_analysis.ipynb                    # EDA & visualizations
│   └── 03_forecasting.ipynb                 # Holt-Winters & Prophet models
├── data/
│   ├── us_renewable_energy_consumption.csv       # Raw data
│   ├── cleaned_us_renewable_energy_no_2024.csv   # Processed (1973–2023)
│   └── cleaned_us_renewable_energy.csv           # Includes partial 2024
├── LICENSE
├── README.md
└── requirements.txt
```

---

**Author:** Huseyin Kucukogul · MIT License
