---
license: cc-by-nc-4.0
language:
  - en
task_categories:
  - text-classification
  - table-question-answering
  - text-retrieval
  - feature-extraction
  - text-generation
tags:
  - food
  - restaurants
  - menus
  - commerce
  - dining
  - food-tech
  - business
  - usa
  - location-data
  - structured-data
  - tabular
  - api-data
size_categories:
  - 10K<n<100K
pretty_name: Souslab — US Restaurant Menus (Sample)
configs:
  - config_name: default
    data_files:
      - split: train
        path: "menu_items_sample.csv"
---

# Souslab — US Restaurant Menus

A structured sample of the Souslab US restaurant menu dataset: real restaurants, real menu items, real prices — normalized into a clean schema you can train on or analyze directly.

This sample is published openly under CC-BY-NC-4.0 for research and non-commercial evaluation. The full dataset — **449,000+ US restaurants and 44.3M+ menu items, refreshed continuously with chain-level aggregation** — is available via the [Souslab API](https://souslab.site) under commercial license.

---

## 🚀 Quick start

```python
from datasets import load_dataset

ds = load_dataset("AnyStackLabsdev/souslab-us-restaurant-menus")
print(ds)
print(ds["train"][0])
```

Or download directly via [Files and versions](https://huggingface.co/datasets/AnyStackLabsdev/souslab-us-restaurant-menus/tree/main).

---

## 📊 What's in this sample

- **Restaurants:** ~4,600 US restaurants
- **Menu items:** ~10,000 menu items
- **Geographic coverage:** All 50 US states + DC
- **Chain coverage:** Independents and chain locations, with chain-level grouping
- **Snapshot date:** 2026-05-29
- **Format:** CSV
- **File size:** ~2.1 MB

This is a **representative sample** — geographically and categorically balanced, but a fraction of the full Souslab corpus. The full dataset is ~4,400x larger.

---

## 🗂️ Schema

### `menu_items_sample.csv`

| Field | Type | Description |
|---|---|---|
| `item_uid` | string | Stable unique identifier for this menu item |
| `restaurant_id` | string | Foreign key — links to the restaurant |
| `menu_name` | string | Name of the menu this item appears on |
| `section_name` | string | Menu section or category (e.g. "Appetizers", "Drinks") |
| `item_name` | string | Display name of the menu item |
| `description` | string \| null | Item description as listed on the menu |
| `price` | float \| null | Price in local currency |
| `price_text` | string \| null | Raw price string as scraped (e.g. "$12.99") |
| `currency` | string | ISO 4217 currency code (e.g. "USD") |
| `out_of_stock` | boolean | Whether the item was marked unavailable at time of snapshot |
| `city_name` | string | City of the restaurant |
| `state_code` | string | US state (2-letter code) |
| `zip` | string | Postal code |
| `geo_lat` | float | Latitude of the restaurant |
| `geo_lng` | float | Longitude of the restaurant |
| `canonical_item_id` | string \| null | Souslab canonical item identifier for cross-restaurant deduplication |

---

## 🧠 Methodology summary

The full methodology lives at [souslab.site/methodology](https://souslab.site/methodology) — covering collection sources, refresh cadence, chain matching, quality controls, and known gaps. Quick version:

- **Sources:** restaurants' own published menus, public aggregator surfaces, and partner data feeds. We don't bypass authentication, scrape behind logins, or ingest user reviews or photos.
- **Chain matching:** multi-signal (registry-anchored, name similarity, location/ownership context, menu signature) — same chain across locations resolves to the same `chain_id`. "Joe's Pizza" in NYC and "Joe's Pizza" in Topeka stay distinct unless ownership/menu signals tie them.
- **Canonical items:** `canonical_item_id` links the same item appearing across multiple sources or snapshots — useful for deduplication and price tracking over time.
- **Refresh cadence (in the live API):** tiered. Top chains daily, mid-tier 2–4× per week, high-traffic independents weekly, long-tail independents monthly.
- **Known gaps:** thin coverage of dine-in independents without digital menus, no nutritional data, no promotional pricing modeling, US-only, English-only.

This sample represents a point-in-time snapshot. The live API is refreshed continuously.

---

## 🎯 Use cases

This dataset is designed for:

- **AI/ML training:** fine-tuning LLMs on food/menu language, training cuisine and dietary classifiers, building food-aware vision/multimodal models, grounding RAG over real-world food knowledge
- **Market research:** pricing analysis, menu trend tracking, regional cuisine prevalence, chain operational analysis
- **Product development:** recommendation engines, menu search and discovery, dietary filtering, food delivery platforms
- **Academic research:** food systems analysis, restaurant economics, regional dining patterns
- **Alt-data signal generation:** restaurant inflation, regional pricing dynamics, chain operational shifts

For commercial deployment, real-time data, larger volumes, or the full 44M+ menu item universe, [contact us for an API license](https://souslab.site).

---

## ⚖️ License

This sample is released under **[CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/)** — free for research and non-commercial use with attribution.

**Commercial use of this sample, or of any derivative dataset or model trained on it, requires a commercial license from Any Stack Labs.** This includes:

- Production deployment in a commercial product or service
- Training models for commercial use (including model-as-a-service)
- Reselling, sublicensing, or distributing derivatives
- Embedding in commercial datasets or research products

For commercial licensing, contact [hello@souslab.site](mailto:hello@souslab.site) or visit [souslab.site](https://souslab.site).

### Attribution

When using this sample in research or other CC-BY-NC contexts, please attribute as:

> *"Data sourced from the Souslab US Restaurant Menus dataset by Any Stack Labs (souslab.site)."*

---

## 📚 Citation

```bibtex
@dataset{souslab_us_restaurant_menus_2026,
  title     = {Souslab US Restaurant Menus (Sample)},
  author    = {{Any Stack Labs}},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/AnyStackLabsdev/souslab-us-restaurant-menus},
  note      = {Sample of the full Souslab dataset; full dataset available via API at souslab.site}
}
```

---

## 🔗 Related

- **Full dataset & API:** [souslab.site](https://souslab.site)
- **API documentation:** [souslab.site/docs](https://souslab.site/docs)
- **Methodology:** [souslab.site/methodology](https://souslab.site/methodology)
- **Any Stack Labs:** [huggingface.co/AnyStackLabsdev](https://huggingface.co/AnyStackLabsdev)

---

## 📬 Contact

- **Commercial licensing & API access:** [hello@souslab.site](mailto:hello@souslab.site)
- **Questions about this sample:** open a discussion on this dataset page
- **Data errors or corrections:** [souslab.site/corrections](https://souslab.site)
- **Restaurant takedown requests:** [souslab.site/takedown](https://souslab.site)

---

## 📝 Changelog

- **v1.0 — 2026-05-29** — Initial public release. ~4,600 restaurants, ~10,000 menu items.

---

*Souslab is built by [Any Stack Labs](https://huggingface.co/AnyStackLabsdev).*