Python Data Visualization Workshop

Create beautiful, interactive data visualizations from Excel files - no prior Python experience required!

Quick Start

1. Install uv (if you don't have it)

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Run the Workshop

# Clone or download this folder, then:
cd excel_demo

# Start the interactive notebook (installs dependencies automatically)
uv run marimo edit workshop.py

That's it! The workshop will open in your browser.

What You'll Learn

Section	Topic	Time
1	Loading Excel data with pandas	10 min
2	Data exploration & filtering	15 min
3	Interactive Plotly charts	25 min
4	Building reactive dashboards	25 min
5	Advanced visualizations	10 min
6	Sharing your work	5 min

Project Structure

excel_demo/
├── workshop.py          # Main marimo notebook (open this!)
├── data/
│   └── sales_data.xlsx  # Sample business data
├── pyproject.toml       # Dependencies (managed by uv)
└── README.md

Using Your Own Data

Replace data/sales_data.xlsx with your own Excel file, then update the file path in the workshop:

df = pd.read_excel("data/your_file.xlsx")

Running as a Web App

To share your dashboard with others:

# Run as interactive web app
uv run marimo run workshop.py

# Export to standalone HTML
uv run marimo export html workshop.py -o dashboard.html

Requirements

• Python 3.12 or 3.13
• That's it! uv handles everything else.

Troubleshooting

"command not found: uv"

• Restart your terminal after installing uv, or run source ~/.bashrc

Charts not showing?

• Make sure you're running with marimo edit, not just python

Want to use your own Python?

# If you prefer pip over uv:
pip install marimo pandas numpy plotly openpyxl
marimo edit workshop.py