US Drug Directory (FDA NDC)
Every drug product marketed in the US in one clean reference table - the FDA National Drug Code directory, flattened. From openFDA's bulk NDC download (~137k products): one fat row per NDC with brand and generic names, active ingredients & strengths, dosage form, route, manufacturer/labeler, pharmacologic class, product type (prescription / OTC) and marketing category. The drug reference table health-tech, pharmacies, formularies and claims pipelines join on. Public domain / CC0.
- Source
- OPENFDA_NDC
- 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
- ~137k US drug products - one clean row per National Drug Code (NDC)
- Brand + generic name, active ingredients & strengths, dosage form, route
- Manufacturer/labeler, pharmacologic class, product type (Rx / OTC), marketing category
- The drug-reference join key for formularies, claims, pharmacy and health-tech
- Product-label data - no PII
- Public domain / CC0 (U.S. FDA openFDA) - free commercial reuse & resale
- Source: U.S. Food and Drug Administration - openFDA (NDC Directory)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| product_ndc | str | National Drug Code (primary key) | 100.0% | 134,284 |
| brand_name | str | Brand / proprietary name | 84.5% | 43,309 |
| generic_name | str | Generic / non-proprietary name | 100.0% | 24,531 |
| labeler_name | str | Manufacturer / labeler | 100.0% | 9,837 |
| product_type | str | Product type (HUMAN PRESCRIPTION / OTC DRUG, …) | 100.0% | 10 |
| dosage_form | str | Dosage form (TABLET, INJECTION, …) | 100.0% | 142 |
| route | str | Route(s) of administration | 100.0% | 195 |
| active_ingredients | str | Active ingredients + strengths | 98.2% | 35,921 |
| pharm_class | str | Pharmacologic class (EPC), where available | 24.0% | 949 |
| marketing_category | str | Marketing category (NDA, ANDA, OTC monograph, …) | 100.0% | 16 |
| marketing_start_date | str | Marketing start date (YYYY-MM-DD) | 100.0% | 9,033 |
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: OPENFDA_NDC (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-drug-ndc-directory_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
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