US Food Portion & Serving Weights
The gram weight of every household measure of a food - '1 cup', '1 tablespoon', '1 slice', '1 medium' → how many grams - the conversion every recipe, nutrition-tracking and dietary app needs and nobody ships cleanly. FoodData Central hides it in food_portion.csv behind a measure-unit lookup with the phrasing split across four columns; we join it (across Foundation, SR Legacy and FNDDS) into one tidy table of (food × household measure → gram weight). Keyed by FDC id so it drops straight next to the nutrition-composition dataset - turn any per-100g nutrient into per-serving. Public domain (U.S. Government work).
- Source
- USDA FDC
- Licence
- Redistributable open data
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- Household measure → grams for tens of thousands of foods (the portion-conversion layer)
- '1 cup', '1 tbsp', '1 slice', '1 medium' … each with its exact gram weight
- Foundation + SR Legacy + FNDDS foods; keyed by FDC id to join the nutrition composition set
- Turn any per-100g nutrient value into a realistic per-serving amount
- Public domain (USDA FoodData Central) - no personal data
- Source: U.S. Department of Agriculture, FoodData Central (public domain)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| fdc_id | int | FoodData Central food id (join key) | 100.0% | 13,044 |
| food | str | Food name / description | 100.0% | 12,877 |
| data_type | str | Source bundle: foundation_food, sr_legacy_food or survey_fndds_food | 100.0% | 3 |
| household_measure | str | Human measure, e.g. '1 cup', '1 slice, thin' | 100.0% | 3,260 |
| gram_weight | float | Weight of that measure in grams | 100.0% | 1,189 |
| amount | float | Numeric quantity of the measure (where given) | 39.9% | 63 |
| modifier | str | Portion modifier / qualifier | 100.0% | 3,043 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: USDA FDC (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("us-food-portion-weights_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
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