legume-nutrient-dashboard 0.1.0

Interactive dashboard for analyzing legume nutrient data from USDA FoodData Central

Legume Nutrient Dashboard

The Legume Nutrient Dashboard is an interactive Streamlit app created for a STAT 386 final project. It collects Foundation-food data from the USDA FoodData Central API (category: "Legumes and Legume Products"), extracts and cleans nutrient information, and provides interactive visualizations for exploration.

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Quickstart

Prerequisites:

• A working Python environment (see pyproject.toml / myenv).
• A USDA API key saved in a file named api.txt at the project root (one-line file containing the key).

1. Sync environment & run tests (project uses uv for environment management):

uv sync
uv run pytest

2. Generate the cleaned dataset

The main script fetches data from the USDA API, extracts nutrients, and writes legus_cleaned.csv.

uv run python main.py

3. Launch the Streamlit dashboard

uv run streamlit run src/legume_nutrient_dashboard/streamlit_app.py

Important: Always run from the project root directory so the app can locate legus_cleaned.csv.

Notes

• The pipeline filters for Data Type: Foundation and Category: Legumes and Legume Products.
• Ensure api.txt exists in the project root before running main.py.

Dashboard Features

• Legume Selector: pick a legume category from the sidebar to filter results.
• Radar Chart: compares average nutrient content across groups (e.g., Protein, Fat, Carbs, Starch, and selected minerals).
• Correlation Heatmap: interactive Plotly heatmap showing nutrient correlations across the dataset.
• Dataset Preview: table view of the cleaned legus_cleaned.csv for inspection.

Technologies Used

• Python: 3.11+ (project environment in myenv)
• Streamlit: dashboard UI
• pandas: data manipulation
• requests: USDA API calls
• regex: nutrient and category extraction
• seaborn / matplotlib: static charts
• plotly: interactive visualizations
• uv: environment & dependency management

Files of interest

• main.py — main pipeline to fetch, clean, and save data
• legus_cleaned.csv — cleaned dataset output
• src/legume_nutrient_dashboard/streamlit_app.py — Streamlit dashboard