Swiggy Restaurants Ahmedabad Dataset
The Swiggy Restaurants Ahmedabad Dataset gives you a complete, structured picture of every restaurant listed for delivery on Swiggy in Ahmedabad. With 1,240 records captured in May 2026, you can explore cuisines, price bands, ratings, delivery promises, and current offers across the city’s vibrant food scene – from Vastrapur to Maninagar. Delivered as a multi‑format […]
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Swiggy Restaurants Ahmedabad Dataset – built for your needs
The Swiggy Restaurants Ahmedabad Dataset gives you a complete, structured picture of every restaurant listed for delivery on Swiggy in Ahmedabad. With 1,240 records captured in May 2026, you can explore cuisines, price bands, ratings, delivery promises, and current offers across the city’s vibrant food scene – from Vastrapur to Maninagar.
Delivered as a multi‑format package (CSV, JSON, XLSX), this dataset plugs instantly into your favourite analytics tools. Whether you’re launching a cloud kitchen, expanding a chain, or analysing Ahmedabad’s food delivery economy, you’ll have the grounded, real‑world data to move fast.
🗂️ Data Schema (10 Columns)
| # | Column Name | Description | Example |
|---|---|---|---|
| 1 | restaurant_name | Restaurant name on Swiggy | Honest Restaurant |
| 2 | locality | Neighbourhood / area | Navrangpura |
| 3 | cuisines | Cuisine tags (comma‑separated) | Gujarati, Punjabi, Thali |
| 4 | avg_cost_for_two_inr | Average cost for two people | ₹600 |
| 5 | rating | Average user rating (1‑5) | 4.1 |
| 6 | delivery_time_min | Est. delivery time (minutes) | 35 |
| 7 | offers | Active discount/promotion | 50% off up to ₹100 |
| 8 | image_url | Restaurant image link | https://… |
| 9 | restaurant_url | Swiggy listing page | https://swiggy.com/ahmedabad/… |
| 10 | last_updated | Snapshot date | 2026-05-15 |
| Image | Discount | Title | Distance | Ratings | Cuisine | Address |
|---|---|---|---|---|---|---|
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/9/1/db0051e9-6acb-4970-a8c9-124a6d654f8b_47589.JPG | 50% OFF UPTO ₹100 | Pizza Hut | 25-30 mins | 4.2 • | Pizzas | Ashram Road |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/10/27/daeaf8d1-b608-4ccd-818f-783ca915c12c_791609.JPG | 50% OFF | Theobroma | 20-25 mins | 4.7 • | Desserts | Navrangpura |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/e0839ff574213e6f35b3899ebf1fc597 | ITEMS AT ₹119 | Chinese Wok | 35-45 mins | 4.3 • | Chinese, Asian, Tibetan, Desserts | CG Road |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/3/17/2e2d52fe-3b10-4f44-8472-06506806e4da_762592.JPG | 50% OFF UPTO ₹100 | Starbucks Coffee | 20-25 mins | 4.4 • | Beverages, Cafe, Snacks, Desserts, Bakery, Ice Cream | Ellis Bridge |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/6/18/213f6e83-e923-4c30-bd12-ebf12aa61ad3_81814.jpg | ITEMS AT ₹55 | Burger King | 25-30 mins | 4.3 • | Burgers, American, Salads, Beverages, Chaat | CG Road |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/10/17/e165861e-b119-4a31-bfa2-227c89fcfc3c_395939.JPG | ITEMS AT ₹179 | KFC | 20-25 mins | 4.2 • | Burgers, Fast Food, Rolls & Wraps | Paldi & Ambawadi |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/10/3/962817a0-7d1c-40c9-81a9-19810cae5e56_70279.JPG | ITEMS AT ₹119 | McDonald's | 35-45 mins | 4.4 • | Burgers, Beverages, Cafe, Desserts | Kankaria |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/ye0cuamd3narriqobmrq | ₹550 OFF ABOVE ₹2499 | Super Dawat Tawa Fry Centre | 20-25 mins | 4.1 • | North Indian, Tandoor, Biryani, Seafood | Navrangpura |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/9/15/78a4fa41-8fc2-4f00-89bd-6e0698677eae_558454.JPG | ₹100 OFF ABOVE ₹199 | La Pino'z Pizza | 25-30 mins | 4.4 • | Pizzas, Pastas, Italian, Desserts, Beverages | Navrangpura |
| https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/6/30/735ca2fa-7c29-4c35-8fb8-d6ca25de34b1_1090048.jpg | ITEMS AT ₹99 | Wow! Momo | 30-35 mins | 4.3 • | Momos, Chinese, fastfood, Asian, Beverages | Vijay Cross Road |
💡 How Businesses Use It
📍 Market Sizing & Gap Analysis
Map restaurant density by locality and cuisine. Find underserved areas ready for new cloud kitchens or delivery brands.
🚀 Delivery Benchmarking
Compare your own delivery times and ratings against Ahmedabad’s top performers to improve SLAs.
🍽️ Menu & Pricing Strategy
Analyse price bands by cuisine and locality to set competitive rates for your own restaurant or franchise.
📊 Forecasting & Expansion
Combine restaurant data with population density to predict demand and prioritise neighbourhood launches.
🎯 Who Relies on This Data?
📈 Food Delivery Platforms
Audit your Ahmedabad restaurant coverage versus Swiggy and identify high‑priority onboarding targets.
🏪 Restaurant Chains & Cloud Kitchens
Enter Ahmedabad with location‑wise data on competition, pricing, and cuisine gaps.
📊 Market Research & Consulting
Build comprehensive reports on Ahmedabad’s food tech landscape, complete with ratings and offer analysis.
🤖 Data Science & AI Teams
Train recommendation systems, delivery‑time prediction models, or restaurant clustering algorithms.
✅ Why Choose ScraperScoop?
The Swiggy Restaurants Ahmedabad Dataset is ethically sourced, cleaned to professional standards, and delivered ready for immediate analysis.
Ethically Collected Public Data
We only extract publicly visible restaurant information. No private profiles or protected content.
Clean & Standardised
Duplicate removals, consistent cuisine names, numeric ratings — you get a spotless dataset.
One‑Time Purchase, Yours Forever
No subscriptions, no recurring fees. Buy once and keep the data.
Fast, Personalised Support
Need a filter for a specific cuisine or locality? Contact us — we respond quickly.
Royalty‑Free Commercial Licence
Use the data in dashboards, reports, ML models, and commercial projects — no extra cost.
Trusted by Food‑Tech Analysts
ScraperScoop data is used by restaurant chains, delivery startups, and market research firms globally.
⭐ What Our Customers Say
"We used the Ahmedabad dataset to pinpoint three locations for our new QSR chain. The locality breakdown saved us weeks of legwork."
"The clean format let me build a Power BI dashboard in hours. Investor‑ready visuals in no time."
"I tested the free 50‑row sample and immediately bought the full dataset. The accuracy was spot‑on."
"ScraperScoop’s team filtered out only pure‑veg restaurants for me. Exceptional support."
📣 Loved the product? Tell us your story.
❓ Frequently Asked Questions
It's a snapshot from May 2026, capturing all delivery‑listed restaurants at that time. You keep the data permanently.
The dataset includes all Ahmedabad localities where Swiggy delivers — Navrangpura, SG Highway, Maninagar, Ellisbridge, Vastrapur, and many more. The `locality` field lets you filter easily.
Absolutely. Request your 50‑row sample and we'll send it right over.
No. This is a one‑time static purchase. If you later need a newer version, you can buy a fresh snapshot.
Yes. The data is collected from public restaurant pages and comes with a royalty‑free commercial licence.
- High-quality, structured dataset
- Regular updates and refresh
- Available in multiple formats
- Free sample before you commit
The same records, in whichever format your stack expects
No conversion step, no separate schema to learn — switch formats any time without touching your pipeline.
{
"id": "12345",
"name": "Sample Product",
"price": 29.99,
"category": "Electronics"
}
]
| id | name | price | category |
|---|---|---|---|
| 12345 | Sample Product | 29.99 | Electronics |
| 67890 | Another Item | 19.50 | Home |
| A · id | B · name | C · price | D · category | |
|---|---|---|---|---|
| 1 | 12345 | Sample Product | 29.99 | Electronics |
| 2 | 67890 | Another Item | 19.50 | Home |
From request to a running data feed
Request a sample
Tell us what you need — no commitment needed.
Review real data
We send a live export so you can validate quality.
Pick a plan
Choose coverage and refresh frequency.
Choose your delivery
JSON, CSV, Excel, S3, or warehouse.
Data keeps flowing
Refreshed on schedule, monitored for changes.
What makes this dataset reliable
Built for anti‑bot measures
Our infrastructure handles the target's specific blocks and markup changes.
Regular refresh where it matters
Key fields update frequently so you're never working with stale data.
One schema, every format
JSON, CSV, and Excel share the same field names and types.
Global coverage
Data from multiple regions, normalized into one clean feed.
99.95% uptime SLA
Backed by a contractual uptime commitment on Growth and Enterprise plans.
A team that answers
Get support from people who know the dataset inside out.
Every field included, in plain terms
| Field | Description | Type |
|---|---|---|
| id | Unique identifier | Core |
| name | Product or entity name | Core |
| price | Current price | Pricing |
| category | Primary category | Core |
| last_updated | Timestamp of most recent refresh | Core |
Priced by coverage, not by seat
Every plan includes JSON, CSV, and Excel delivery, plus a free sample before you commit.
Sample
Validate schema and quality before buying.
- Real, current data
- JSON, CSV, or Excel
- Delivered within 1 business day
Starter
A defined set of records, daily refresh.
- 1 region
- Daily refresh
- JSON, CSV & Excel delivery
- Email support
Growth
Multi-region coverage with hourly options.
- Up to 5 regions
- Hourly refresh on key fields
- Warehouse & S3 delivery
- Chat & email support, <4h
Enterprise
Full catalog, custom SLA.
- All regions
- 99.95% uptime SLA
- Dedicated account manager
- Custom schema fields on request
Get it however your team already works
Dataset vs. an in‑house scraper
| Capability | ScraperScoop Dataset | In‑house scraper |
|---|---|---|
| Time to first data | Same day (sample) | Weeks to months |
| Anti‑bot handling | ||
| Multi‑region coverage | ||
| Maintenance when source changes | Handled for you | Your team's responsibility |
| Excel‑ready export |
Teams that stopped guessing and started using data
"The sample matched our production needs almost exactly. We were loading real data into our warehouse within two days."
"Excel export mattered more than I expected — our team could work with the data directly without asking engineering for a CSV parser."
"The refresh speed on key fields changed how fast we could react to competitors. Absolutely essential."
Questions about this dataset
See real data before you decide anything
Request a free sample and validate the dataset against your specific needs.
No commitment required to see real data first.
