A field guide to Restaurant data in New York City, New York

A map can show nearby businesses in seconds, but a market view needs more context. Category labels, review signals, coordinates, and timestamps make the pattern easier to evaluate.

The numbers behind this local view

This article uses a random 80,000-record sample from the operational listings in our US POI collection. After filtering for numeric ratings and review counts, the sample contained 25 Restaurant records associated with New York City, New York. Their average public rating was 4.50, with 18,910 reviews in total — roughly 756 reviews per record.

That is a sample statistic, not a census of every Restaurant in the city. It gives teams a consistent way to compare local categories without pretending that one snapshot is the whole market.

Representative records in the sample

• SAPERAVI UES — 5.0 rating, 770 reviews
• Chick N’ Baos — 4.9 rating, 225 reviews
• HALAL & CO. — 4.9 rating, 10 reviews

These examples were selected from records crawled around August 29, 2026. They show the name, category, rating, review, address, coordinate, and status fields available in a structured POI record. They are not endorsements, rankings, or promises about current availability.

Where the data becomes useful

For directory operators, this is a starting point for deduplication, address validation, and category normalization. Analysts can join it with polygons, drive-time areas, or first-party data.

Read the numbers with care

Ratings, reviews, opening hours, and operating status change. City labels can also reflect a source-defined metro area rather than a strict municipal boundary. Validate current source information before a record is used in customer-facing content or operational decisions.

Explore US POI datasets to build location-data workflows around state, city, category, coordinates, and business signals.