An expanding collection of data scrapers designed to gather location details on prominent stores, restaurants and other consumer destinations across the United States.
Company category | Companies | Locations |
---|---|---|
Automotive | 3 | 2,924 |
Banking | 1 | 6,066 |
Beauty Products | 2 | 3,013 |
Casual Dining | 4 | 3,567 |
Clothing & Accessories | 3 | 620 |
Coffee Shops & Desserts | 5 | 22,788 |
Electronics & Appliances | 1 | 526 |
Entertainment | 2 | 868 |
Fast Food & Quick Service | 21 | 92,505 |
Food & Beverage | 2 | 236 |
Frozen Yogurt | 3 | 529 |
Home Improvement | 1 | 2,002 |
Jewelry | 1 | 234 |
Pet Supplies | 1 | 121 |
Retail Stores | 20 | 64,340 |
Shoes & Accessories | 1 | 439 |
Specialty Foods | 5 | 1856 |
Total collected | 76 | 202,664 |
Company | Category | Locations |
---|---|---|
7-Eleven | Fast Food & Quick Service | 8,568 |
99 Ranch Market | Specialty Foods | 62 |
99 Cents Only | Retail Stores | 370 |
Abercrombie & Fitch | Clothing & Accessories | 221 |
Aldi | Retail Stores | 2,362 |
AMC theaters | Entertainment | 554 |
Apple Stores | Electronics & Appliances | 526 |
Arby's | Fast Food & Quick Service | 3,388 |
Au Bon Pain | Food & Beverage | 71 |
Bank of America | Banking | 6,066 |
Bass Pro/Cabela's | Retail Stores | 155 |
Buc-ee's | Retail Stores | 47 |
Carl's Jr. | Fast Food & Quick Service | 1,026 |
Chick-Fil-A | Fast Food & Quick Service | 2,896 |
Chili's | Casual Dining | 1,229 |
Chipotle | Fast Food & Quick Service | 3,385 |
Cinemark theaters | Entertainment | 314 |
Costco | Retail Stores | 588 |
California Pizza Kitchen | Casual Dining | 121 |
Cracker Barrel | Casual Dining | 662 |
Crumbl | Coffee Shops & Dessert | 1,717 |
Culver's | Fast Food & Quick Service | 794 |
CVS | Retail Stores | 9,333 |
Del Taco | Fast Food & Quick Service | 328 |
Dollar General | Retail Stores | 19,780 |
Dollar Tree | Retail Stores | 8,159 |
DSW | Shoes & Accessories | 439 |
Dunkin Donuts | Fast Food & Quick Service | 9,538 |
El Pollo Loco | Fast Food & Quick Service | 500 |
Family Dollar | Retail Stores | 8,389 |
Ford dealers | Automotive | 2,901 |
Forever 21 | Retail Stores | 380 |
Giant Food Stores | Food & Beverage | 165 |
Hardee's | Fast Food & Quick Service | 1,419 |
Hmart | Specialty Foods | 80 |
Hollister | Clothing & Accessories | 104 |
Home Depot | Home Improvement | 2,002 |
Hyundai dealers | Automotive | 833 |
In-N-Out Burger | Fast Food & Quick Service | 401 |
Jared | Jewelry | 234 |
JCPenney | Retail Stores | 663 |
Kentucky Fried Chicken | Fast Food & Quick Service | 4,276 |
King Taco | Fast Food & Quick Service | 21 |
Krispy Kreme | Coffee Shops & Desserts | 4,646 |
Kroger | Retail Stores | 1,244 |
Kung Fu Tea | Coffee Shops & Desserts | 425 |
Macy's | Retail Stores | 520 |
McDonald's | Fast Food & Quick Service | 11,197 |
Menchies | Frozen Yogurt | 324 |
Nike Stores | Clothing & Accessories | 295 |
Nordstrom | Clothing & Accessories | 358 |
Olive Garden | Casual Dining | 911 |
PetSmart | Pet Supplies | 121 |
Pei Wei | Specialty Foods | 1,544 |
Pinkberry | Frozen Yogurt | 70 |
Pizza Hut | Fast Food & Quick Service | 5,204 |
Pollo Tropical | Fast Food & Quick Service | 126 |
Publix | Retail Stores | 1,407 |
Red Lobster | Casual Dining | 671 |
Safeway | Retail Stores | 865 |
Sephora | Beauty Products | 1,602 |
Sonic | Fast Food & Quick Service | 3,529 |
Shipley Do-Nuts | Coffee Shops & Desserts | 374 |
Subway | Fast Food & Quick Service | 21,229 |
Superior Grocers | Retail Stores | 73 |
Starbucks | Coffee Shops & Desserts | 16,288 |
Taco Bell | Fast Food & Quick Service | 7,148 |
TCBY | Frozen Yogurt | 135 |
Torchy's Tacos | Specialty Foods | 124 |
Trader Joe's | Retail Stores | 558 |
Ulta | Beauty Products | 1,411 |
Vons | Retail Stores | 186 |
Wahoo's | Specialty Foods | 46 |
Walgreens | Retail Stores | 8,446 |
Wawa | Retail Stores | 860 |
Wendy's | Fast Food & Quick Service | 6,150 |
Whataburger | Fast Food & Quick Service | 1,014 |
Wienerschnitzel | Fast Food & Quick Service | 320 |
This repository serves as a non-commercial project to practice data scraping skills (though sometimes the data ends up getting published). The scrapers get location data from the store lookup directories found on each company’s website. While the findings are consistent with public estimates and company disclosures about inventory levels, they likely aren't complete, as locations open and close and some may have been unintentionally missed in the scraping process.
Please let me know if you have questions or concerns — or if there's a company you'd like to see on this list.
Before you begin, ensure you have the following installed on your system:
- Python 3.10
- Jupyter Lab
We recommend using a virtual environment for Python projects. For this repo, pipenv
is the chosen manager.
Follow these steps to prepare your environment:
First, clone this repository to your local machine and navigate into it using your terminal:
git clone <repository-url>
cd <repository-name>
Inside the repository directory, initiate a virtual environment using pipenv:
pipenv shell
This command creates a virtual environment and activates it.
Install the required dependencies, including Pandas, Geopandas and others, with the following command:
pipenv install
With your environment set up and dependencies installed, you are ready to start working with the notebooks:
jupyter lab
This command launches Jupyter Lab in your browser, where you can open, edit and run the notebooks.
Please be mindful of each company's service terms and also polite to its servers.