---
license: cc-by-nc-4.0
pretty_name: RoasterDB — Specialty Coffee Dataset (Free Sample)
tags:
- coffee
- food
- e-commerce
- flavor
- sca-flavor-wheel
- recommender-systems
size_categories:
- n<1K
---

# ☕ RoasterDB — Specialty Coffee Dataset (Free Sample)

A **free sample** of RoasterDB: a structured dataset of specialty-coffee products scraped from the **direct storefronts** of curated artisan roasters worldwide, with tasting notes normalized to the **Specialty Coffee Association (SCA) Flavor Wheel** and a **source URL on every record** so any fact can be re-verified.

**This sample contains 100 verified-tier records across 72 roasters** — a real taste of the schema and quality.

The **full dataset covers 8,000+ products, 280+ roasters, 20+ countries, and 11,000+ SCA flavor mappings** (SQLite · CSV · JSON).

## Get the Full Dataset

* 🔗 **Official Portal:** [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev) — full snapshot $99 one-time
* 🏆 **Kaggle:** [RoasterDB Specialty Coffee Sample](https://www.kaggle.com/datasets/ahtiticheamine/roasterdb-specialty-coffee-sample)
* 🔄 **Live scraping (self-serve):** [Specialty Coffee Roaster Scraper on Apify](https://apify.com/dataengineered/specialty-coffee-roaster-scraper) — pay-per-result
* ☕ **Interactive Explorer:** [Dataset Sample Explorers Space — RoasterDB tab](https://huggingface.co/spaces/Ichlibitiche/dataset-sample-explorers)

## Key Columns

| Column | Description |
| :--- | :--- |
| `product_id`, `title`, `source_roaster` | Product identity |
| `origin_country`, `origin_region`, `altitude_min/max_meters` | Origin, where stated |
| `process_method`, `roast_level`, `varietals` | Processing attributes |
| `weight_grams`, `price_currency`, `price_value` | Unit and sanitized price |
| `tasting_notes_sca_nodes` | `; `-separated SCA wheel paths, e.g. `Fruity > Berry > Blueberry` |
| `quality_flag` | `good` (verified tier) or `questionable` |
| `source_url`, `retrieved_at`, `dataset_version` | Full provenance — every record re-verifiable |

Coverage is honest and uneven — storefronts don't all publish farm-level data. Full field coverage numbers are documented at [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev).

## Quick Start

```python
import pandas as pd

df = pd.read_csv("hf://datasets/Ichlibitiche/roasterdb-specialty-coffee-sample/roasterdb_sample.csv")
print(len(df), "coffees from", df["source_roaster"].nunique(), "roasters")
# → 100 coffees from 72 roasters
```

## Use Cases

- Coffee subscription & recommendation apps (structured product + flavor data)
- Flavor-based search and discovery on the SCA graph
- ML / RAG corpora over specialty coffee
- Market & assortment research across roasters, origins, and price bands

## License

Sample data: **CC BY-NC 4.0** — free to use with attribution, non-commercial. The full dataset is available under a commercial license at [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev). Questions or roaster removal requests: `RoasterDB@proton.me`.