📊 Soul Foods Pink Morsel Sales Visualizer

Interactive data visualization dashboard built with Python Dash to explore regional sales trends and answer a business question:

Were sales higher before or after the Pink Morsel price increase on Jan 15, 2021?

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Preview

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🚀 Features

• Data cleaning & transformation with Pandas
• Interactive line chart using Plotly
• Region filtering via radio buttons
• Styled responsive UI
• Automated UI testing with Pytest + Dash Testing

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🛠 Tech Stack

• Python 3.9
• Dash
• Plotly
• Pandas
• Pytest
• Selenium (Dash testing)

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📈 Running the App

Clone repo

git clone https://github.com/swati048/quantium-starter-repo.git
cd quantium-starter-repo

Create virtual environment

python -m venv venv
venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run dashboard

python app.py

Visit:

http://127.0.0.1:8050

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🧪 Run Tests

pytest

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CI Script

#Run automated tests via:
./run_tests.sh

⚙️ Continuous Integration (GitHub Actions)

This project uses GitHub Actions for automated Continuous Integration. Every time code is pushed or a pull request is opened against main, the workflow defined in:

.github/workflows/ci.yml

runs automatically to ensure the application remains stable.

What the CI Pipeline Does

1️⃣ Checks out the repository 2️⃣ Sets up Python 3.9 3️⃣ Installs project dependencies 4️⃣ Installs Chrome for browser-based Dash testing 5️⃣ Installs ChromeDriver automatically 6️⃣ Runs the full Pytest test suite

If all tests pass ✔️ → build succeeds If any test fails ❌ → build fails immediately

This ensures:

• UI components remain functional
• Dashboard doesn’t break after changes
• Regressions are caught early
• Industry-standard development workflow

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🐛 Troubleshooting

"selenium.common.exceptions.WebDriverException"

# This command finds the driver path and adds it to your current session
$env:PATH += ";$(python -c 'from webdriver_manager.chrome import ChromeDriverManager; print(ChromeDriverManager().install())' | Split-Path)"

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📊 Business Insight

From the visualization, sales trends before and after the price change can be compared interactively by region, enabling data-driven decision making.

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👩‍💻 Author

Swati Thakur

• GitHub: @swati048
• LinkedIn: Swati Thakur
• Email: thakurswati048@gmail.com

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⭐ Star this repository if you found it helpful! ⭐

Made with ❤️ and 🐍 Python