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It provides REST access to FoodData Central (FDC). It is intended primarily to assist application developers wishing to incorporate nutrient data into their applications or websites.
Engineers use the USDA FoodData Central API with `requests` and an API key, querying the `/food/{fdcId}` and `/foods/search` endpoints. Nutrient data is parsed from nested JSON into pandas DataFrames for nutritional analysis and food classification models.
FoodData Central enables AI-powered nutrition assistants that answer 'How much protein is in a cup of cooked lentils?' with USDA-verified data. RAG pipelines built on this dataset ground dietary chatbots in authoritative nutritional science rather than hallucinated values.
# pip install requests pandas
import requests, pandas as pd
resp = requests.get(
"https://api.nal.usda.gov/fdc/v1/foods/search",
params={"query": "avocado", "pageSize": 5, "api_key": "YOUR_API_KEY"}
)
foods = resp.json()["foods"]
df = pd.DataFrame([{"description": f["description"],
"calories": next((n["value"] for n in f.get("foodNutrients", [])
if n["nutrientName"] == "Energy"), None)}
for f in foods])
print(df)Official dataset source
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