Optional: Resources

We'll introduce a lot of powerful tools. Find the ones that interest you and explore them further.

Marimo Resources

Marimo is a powerful new reactive app option for Python.

• Marimo Documentation
• Marimo for Learners
• Marimo Primer for Education

Marimo also includes interactive tutorials. From the project folder, run:

uv run marimo tutorial intro

Jupyter Notebook Resources

• Project Jupyter
• Jupyter Notebook Documentation
• VS Code Jupyter Documentation

Jupyter Shortcut Keys

Press Esc to enter command mode (cell border turns blue), then:

• Shift + Enter: Run the current cell and move to the next one.
• Ctrl + Enter: Run the current cell without moving.
• A: Insert a new cell above.
• B: Insert a new cell below.
• M: Change cell to Markdown.
• Y: Change cell to Code.

Numpy and pandas

These are key libraries for data analysis. Pandas is built on NumPy arrays. Pandas has some new competitors in big data - you might check out polars.

Matplotlib

Matplotlib is the core plotting library for Python. If you enjoy data visualization and want to excel, spend some time understanding this key library.

Seaborn Charts

Do a search for Seaborn Gallery to see examples of charts you can create with Seaborn. Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

EDA VizKit

EDA VizKit provides reusable examples of professional Python code for exploratory data visualization.

Explore the source code if curious how simple visualization functions can be organized and reused.

Community Resilience (NIST TraCR)

For more examples of reactive charting (with Python, marimo, Altair, Plotly, and Matplotlib), see the following.

Each repository uses the same layered architecture. To point an app at a different dataset, rewrite its s00 source adapter so the output matches the canonical schema. Everything from s01 onward keeps working.

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