⚡ EV Charging Analytics Dashboard

Production-style Streamlit dashboard for exploring global EV charging infrastructure with Plotly and PyDeck.
The repo is structured as a package (src/), with automated checks (Ruff) and a test suite (Pytest).

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🎥 Live Preview

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📌 Overview

This dashboard explores the Global EV Charging Stations & Models Dataset (2025):

• 🌍 242k+ charging stations across 121 countries
• 🎛️ Filters: country, power class, fast-DC, ports
• 📊 KPIs and distribution insights (including Lorenz curve + Gini)
• 🗺️ Interactive world map with clustering
• 🧮 Allocation optimizer for fast-DC expansion scenarios

📦 Dataset repository:

• https://github.com/tarekmasryo/Global-EV-Charging-Stations

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🖼️ Screenshots

Overview

Map

Insights

Optimizer

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🔑 Key Features

• 🎛️ Country/city/power-class filters
• 📈 KPIs: total stations, ports, avg kW, fast-DC share
• 📊 Visuals: donut charts, bar charts, Lorenz curve + Gini
• 🧮 Optimizer: simulate allocation of new fast-DC ports
• 🧭 Compare mode: selected slice vs global

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🧱 Project Structure

.
├── app.py
├── src/ev_charging_dashboard/
│   ├── analytics.py
│   ├── data.py
│   ├── services.py
│   └── ...
├── tests/
├── assets/
├── requirements.txt
├── requirements-dev.txt
└── pyproject.toml

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🚀 Run Locally

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -U pip
python -m pip install -r requirements.txt
streamlit run app.py

Notes:

• requirements.txt installs the local package in editable mode (-e .) so ev_charging_dashboard imports work out of the box.
• If PowerShell blocks activation: Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass

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⚙️ Data Configuration

The app auto-loads the dataset from the public GitHub raw CSV by default.
You can override the data source in any of the following ways (highest priority first):

1. 🔗 Query param: ?csv=<path_or_url>
2. 🔐 Streamlit secrets (.streamlit/secrets.toml):

DATA_URL = "https://raw.githubusercontent.com/tarekmasryo/Global-EV-Charging-Stations/main/data/charging_station.csv"

3. 🌱 Environment variables (first one found is used): CSV_URL, CSV_PATH, DATA_URL

Optional enrichment files:

• 🌐 world_population.csv
• 🧭 country_region.csv

If these files are not present, related enrichment metrics will be skipped gracefully.

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☁️ Deploy (Streamlit Community Cloud)

1. Push this repository to GitHub.
2. Create a new Streamlit Cloud app from the repo.
3. Set DATA_URL in Streamlit Secrets (recommended), or rely on the default auto-load URL.

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🧪 Development

Install dev tools:

pip install -r requirements-dev.txt
pre-commit install

Run checks:

ruff check .
ruff format .
pytest -q

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📜 License & Attribution

• ✅ Code: Apache-2.0 (see LICENSE)
• ✅ Dataset: hosted in the dataset repository (see link above)

If you use the dashboard or dataset, please credit:

Global EV Charging Dashboard and Dataset by Tarek Masryo.