By clicking the “I agree” checkbox below, you: (a) represent that if you are using the dataset on behalf of an organization (e.g., your employer or other entity), you are agreeing on behalf of that organization; (b) agree to allow repository authors to use your employer or entity name and logo in descriptions of its partners on its website, in media, and in marketing materials.

Foursquare OS Places is now a gated dataset on Hugging Face. Read more about why we are making this change here: https://medium.com/@foursquare/evolving-fsq-os-places-fa7a3f5197cd

Access FSQ OS Places

With Foursquare’s Open Source Places, you can access free data to accelerate geospatial innovation and insights. View the Places OS Data Schemas for a full list of available attributes.

Prerequisites

In order to access Foursquare's Open Source Places data, it is recommended to use Spark. Here is how to load the Places data in Spark from Hugging Face.

For Spark 3, you can use the read_parquet helper function from the HF Spark documentation. It provides an easy API to load a Spark Dataframe from Hugging Face, without having to download the full dataset locally:
```
places = read_parquet("hf://datasets/foursquare/fsq-os-places/release/dt=2025-10-14/places/parquet/*.parquet")
```
For Spark 4, there will be an official Hugging Face Spark data source available.

Alternatively you can download the following files to your local disk or cluster:

Parquet Files:
- Places - release/dt=2025-10-14/places/parquet
- Categories - release/dt=2025-10-14/categories/parquet

Hugging Face provides the following download options.

Example Queries

The following are examples on how to query FSQ Open Source Places using Athena and Spark:

Filter Categories by the parent level
Filter out non-commercial venues
Find open and recently active POI

Filter by Parent Level Category

SparkSQL

WITH places_exploded_categories AS (
  -- Unnest categories array
  SELECT fsq_place_id, 
         name, 
         explode(fsq_category_ids) as fsq_category_id 
  FROM places
),
 distinct_places AS (
  SELECT 
    DISTINCT(fsq_place_id) -- Get distinct ids to reduce duplicates from explode function
  FROM places_exploded_categories p 
  JOIN categories c -- Join to categories to filter on Level 2 Category
  ON p.fsq_category_id = c.category_id 
  WHERE c.level2_category_id = '4d4b7105d754a06374d81259' -- Restaurants
)
SELECT * FROM places
WHERE fsq_place_id IN (SELECT fsq_place_id FROM distinct_places)

Filter out Non-Commercial Categories

SparkSQL

SELECT * FROM places
WHERE arrays_overlap(fsq_category_ids, array('4bf58dd8d48988d1f0931735',	-- Airport Gate 
'62d587aeda6648532de2b88c',	-- Beer Festival 
'4bf58dd8d48988d12b951735',	-- Bus Line 
'52f2ab2ebcbc57f1066b8b3b',	-- Christmas Market 
'50aa9e094b90af0d42d5de0d',	-- City 
'5267e4d9e4b0ec79466e48c6',	-- Conference 
'5267e4d9e4b0ec79466e48c9',	-- Convention 
'530e33ccbcbc57f1066bbff7',	-- Country 
'5345731ebcbc57f1066c39b2',	-- County 
'63be6904847c3692a84b9bb7',	-- Entertainment Event 
'4d4b7105d754a06373d81259',	-- Event 
'5267e4d9e4b0ec79466e48c7',	-- Festival 
'4bf58dd8d48988d132951735',	-- Hotel Pool 
'52f2ab2ebcbc57f1066b8b4c',	-- Intersection 
'50aaa4314b90af0d42d5de10',	-- Island 
'58daa1558bbb0b01f18ec1fa',	-- Line 
'63be6904847c3692a84b9bb8',	-- Marketplace 
'4f2a23984b9023bd5841ed2c',	-- Moving Target 
'5267e4d9e4b0ec79466e48d1',	-- Music Festival 
'4f2a25ac4b909258e854f55f',	-- Neighborhood 
'5267e4d9e4b0ec79466e48c8',	-- Other Event 
'52741d85e4b0d5d1e3c6a6d9',	-- Parade 
'4bf58dd8d48988d1f7931735',	-- Plane 
'4f4531504b9074f6e4fb0102',	-- Platform 
'4cae28ecbf23941eb1190695',	-- Polling Place 
'4bf58dd8d48988d1f9931735',	-- Road 
'5bae9231bedf3950379f89c5',	-- Sporting Event 
'530e33ccbcbc57f1066bbff8',	-- State 
'530e33ccbcbc57f1066bbfe4',	-- States and Municipalities 
'52f2ab2ebcbc57f1066b8b54',	-- Stoop Sale 
'5267e4d8e4b0ec79466e48c5',	-- Street Fair 
'53e0feef498e5aac066fd8a9',	-- Street Food Gathering 
'4bf58dd8d48988d130951735',	-- Taxi 
'530e33ccbcbc57f1066bbff3',	-- Town 
'5bae9231bedf3950379f89c3',	-- Trade Fair 
'4bf58dd8d48988d12a951735',	-- Train 
'52e81612bcbc57f1066b7a24',	-- Tree 
'530e33ccbcbc57f1066bbff9',	-- Village
)) = false

Find Open and Recently Active POI

SparkSQL

SELECT * FROM places p
WHERE p.date_closed IS NULL
    AND p.date_refreshed >= DATE_SUB(current_date(), 365);

Licensing information

The dataset is available under the Apache 2.0 license

Appendix

Non-Commercial Categories Table

Category Name	Category ID
Airport Gate	4bf58dd8d48988d1f0931735
Beer Festival	62d587aeda6648532de2b88c
Bus Line	4bf58dd8d48988d12b951735
Christmas Market	52f2ab2ebcbc57f1066b8b3b
City	50aa9e094b90af0d42d5de0d
Conference	5267e4d9e4b0ec79466e48c6
Convention	5267e4d9e4b0ec79466e48c9
Country	530e33ccbcbc57f1066bbff7
County	5345731ebcbc57f1066c39b2
Entertainment Event	63be6904847c3692a84b9bb7
Event	4d4b7105d754a06373d81259
Festival	5267e4d9e4b0ec79466e48c7
Hotel Pool	4bf58dd8d48988d132951735
Intersection	52f2ab2ebcbc57f1066b8b4c
Island	50aaa4314b90af0d42d5de10
Line	58daa1558bbb0b01f18ec1fa
Marketplace	63be6904847c3692a84b9bb8
Moving Target	4f2a23984b9023bd5841ed2c
Music Festival	5267e4d9e4b0ec79466e48d1
Neighborhood	4f2a25ac4b909258e854f55f
Other Event	5267e4d9e4b0ec79466e48c8
Parade	52741d85e4b0d5d1e3c6a6d9
Plane	4bf58dd8d48988d1f7931735
Platform	4f4531504b9074f6e4fb0102
Polling Place	4cae28ecbf23941eb1190695
Road	4bf58dd8d48988d1f9931735
State	530e33ccbcbc57f1066bbff8
States and Municipalities	530e33ccbcbc57f1066bbfe4
Stopp Sale	52f2ab2ebcbc57f1066b8b54
Street Fair	5267e4d8e4b0ec79466e48c5
Street Food Gathering	53e0feef498e5aac066fd8a9
Taxi	4bf58dd8d48988d130951735
Town	530e33ccbcbc57f1066bbff3
Trade Fair	5bae9231bedf3950379f89c3
Train	4bf58dd8d48988d12a951735
Tree	52e81612bcbc57f1066b7a24
Village	530e33ccbcbc57f1066bbff9

Downloads last month: 1,405

Models trained or fine-tuned on foursquare/fsq-os-places