McDonald's Locations dataset (June 2026)
21,307 locations across 27 countries and 8,854 cities, with 11 fields per row. Available in CSV and ZIP formats.
- Rows
- 21,307
- Fields
- 11
- Countries
- 27
- Collected
- Jun 2026
License
Licensed under CC BY 4.0. Requires attribution. License & attribution guide →
Fields
| # | Column | Field |
|---|---|---|
| 1 | outlet_id | Outlet ID |
| 2 | outlet_name | Outlet Name |
| 3 | country_code | Country Code |
| 4 | country | Country |
| 5 | city | City |
| 6 | region | Region |
| 7 | zip_code | ZIP Code |
| 8 | address Premium | Address |
| 9 | coordinates | Coordinates |
| 10 | phone_number Premium | Phone Number |
| 11 | opening_hours Premium | Opening Hours |
Sample rows
The first 5 rows, straight out of the file.
| outlet_id | outlet_name | country_code | country | city | region | zip_code | address Premium | coordinates | phone_number Premium | opening_hours Premium |
|---|---|---|---|---|---|---|---|---|---|---|
| US:243795 | Idaho Falls - Northgate Mile | US | United States | Idaho Falls | Idaho | 83401 | 1575 N Gate Mile | [43.51063,-112.01800] | +1 208 524 2757 | Mo-Th 05:30-00:30; Fr-Sa 05:30-01:00; Su 06:00-23:00 |
| US:243801 | Boise Main St. | US | United States | Boise | Idaho | 83702 | 2510 Fairview Ave | [43.62120,-116.22153] | +1 208 344 9040 | Mo-Sa 05:00-23:30; Su 06:00-23:00 |
| US:243849 | Chgo-2425 E 79th | US | United States | Chicago | Illinois | 60649 | 2425 E 79th St | [41.75137,-87.56535] | +1 773 768 0153 | Mo-Su 00:00-24:00 |
| US:243856 | Chgo-4320 Cicero | US | United States | Chicago | Illinois | 60641 | 4320 N Cicero | [41.95928,-87.74790] | +1 773 657 3550 | Mo-Su 06:00-23:00 |
| US:243771 | Eagle Plaza | US | United States | Eagle | Idaho | 83616 | 178 S Eagle Rd | [43.69336,-116.35360] | +1 208 938 0031 | Mo-Th 06:30-23:00; Fr-Sa 06:30-24:00; Su 06:00-23:00 |
Get the full dataset (Free)
In the free version, coordinates are rounded to two decimal places (1 km precision) and premium fields are not available.
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Use it directly
Only meant for experimentation. Using it directly in production pipeline is strictly prohibited.
Python
import pandas as pd
df = pd.read_csv("https://bizlocationdb.com/locations/mcdonalds?download=csv")
print(df.head())DuckDB
SELECT country, count(*) AS n
FROM read_csv('https://bizlocationdb.com/locations/mcdonalds?download=csv')
GROUP BY 1 ORDER BY n DESC;