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This dataset covers 6,288 verified records spread across 79+ districts in Uttar Pradesh. 6,288 records carry a verified phone number and 2,201 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Sonbhadra (1,270 listings), Basti (635 listings), Auraiya (423 listings), Allahabad (317 listings), Agra (254 listings), Hardoi (212 listings), Shamli (181 listings), and Ambedkar Nagar (159 listings).
Additional coverage spans Bahraich (141), Chandauli (127), Sultanpur (115), Lalitpur (106), Pratapgarh (98), Firozabad (91), Sitapur (85), Varanasi (79), Kheri (75), Gorakhpur (71), Maharajganj (67), Kanpur Dehat (63) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Sonbhadra | 1,270 | 1,270 | 445 |
| Basti | 635 | 635 | 222 |
| Auraiya | 423 | 423 | 148 |
| Allahabad | 317 | 317 | 111 |
| Agra | 254 | 254 | 89 |
| Hardoi | 212 | 212 | 74 |
| Shamli | 181 | 181 | 63 |
| Ambedkar Nagar | 159 | 159 | 56 |
| Bahraich | 141 | 141 | 49 |
| Chandauli | 127 | 127 | 44 |
| All districts (79) | 6,288 | 6,288 | 2,201 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Sonbhadra | 1,270 | 1,270 | 445 |
| Basti | 635 | 635 | 222 |
| Auraiya | 423 | 423 | 148 |
| Allahabad | 317 | 317 | 111 |
| Agra | 254 | 254 | 89 |
| Hardoi | 212 | 212 | 74 |
| Shamli | 181 | 181 | 63 |
| Ambedkar Nagar | 159 | 159 | 56 |
| Bahraich | 141 | 141 | 49 |
| Chandauli | 127 | 127 | 44 |
| Sultanpur | 115 | 115 | 40 |
| Lalitpur | 106 | 106 | 37 |
| Pratapgarh | 98 | 98 | 34 |
| Firozabad | 91 | 91 | 32 |
| Sitapur | 85 | 85 | 30 |
| Varanasi | 79 | 79 | 28 |
| Kheri | 75 | 75 | 26 |
| Gorakhpur | 71 | 71 | 25 |
| Maharajganj | 67 | 67 | 23 |
| Kanpur Dehat | 63 | 63 | 22 |
| Siddharthnagar | 60 | 60 | 21 |
| Unnao | 58 | 58 | 20 |
| Hamirpur | 55 | 55 | 19 |
| Jaunpur | 53 | 53 | 19 |
| Mainpuri | 51 | 51 | 18 |
| Ballia | 49 | 49 | 17 |
| Banda | 47 | 47 | 16 |
| Barabanki | 45 | 45 | 16 |
| Mathura | 44 | 44 | 15 |
| Pilibhit | 42 | 42 | 15 |
| Bulandshahr | 41 | 41 | 14 |
| Sambhal | 40 | 40 | 14 |
| Kanpur Nagar | 38 | 38 | 13 |
| Amethi | 37 | 37 | 13 |
| Saharanpur | 36 | 36 | 13 |
| Deoria | 35 | 35 | 12 |
| Mau | 34 | 34 | 12 |
| Azamgarh | 33 | 33 | 12 |
| Chitrakoot | 33 | 33 | 12 |
| Muzaffarnagar | 32 | 32 | 11 |
| Gautam Buddha Nagar | 31 | 31 | 11 |
| Gonda | 30 | 30 | 11 |
| Budaun | 30 | 30 | 11 |
| Bareilly | 29 | 29 | 10 |
| Aligarh | 28 | 28 | 10 |
| Etah | 28 | 28 | 10 |
| Baghpat | 27 | 27 | 9 |
| Kushinagar | 26 | 26 | 9 |
| Prayagraj | 26 | 26 | 9 |
| Fatehpur | 25 | 25 | 9 |
| Farrukhabad | 25 | 25 | 9 |
| Shrawasti | 24 | 24 | 8 |
| Moradabad | 24 | 24 | 8 |
| Raebareli | 24 | 24 | 8 |
| Bijnor | 23 | 23 | 8 |
| Hathras | 23 | 23 | 8 |
| Rampur | 22 | 22 | 8 |
| Kanpur | 22 | 22 | 8 |
| Mirzapur | 22 | 22 | 8 |
| Balrampur | 21 | 21 | 7 |
| Shravasti | 21 | 21 | 7 |
| Etawah | 20 | 20 | 7 |
| Meerut | 20 | 20 | 7 |
| Lucknow | 20 | 20 | 7 |
| Sant Kabir Nagar | 20 | 20 | 7 |
| Amroha | 19 | 19 | 7 |
| Kasganj | 19 | 19 | 7 |
| Jalaun | 19 | 19 | 7 |
| Bhadohi | 18 | 18 | 6 |
| Ghaziabad | 18 | 18 | 6 |
| Mahoba | 18 | 18 | 6 |
| Shahjahanpur | 18 | 18 | 6 |
| Ghazipur | 17 | 17 | 6 |
| Hapur | 17 | 17 | 6 |
| Ayodhya | 17 | 17 | 6 |
| Kaushambi | 17 | 17 | 6 |
| Lakhimpur Kheri | 16 | 16 | 6 |
| Kannauj | 16 | 16 | 6 |
| Jhansi | 16 | 16 | 6 |
| All districts (79) | 6,288 | 6,288 | 2,201 |
The Fitness Centers database for Uttar Pradesh, India includes 6,288+ verified businesses with company name, address, city, state, phone, email, website and GPS coordinates. The file is delivered as a CSV ready for CRM import or BI analysis.
Akhil (IN) bought 1 week ago · Obaid (IN) bought 2 weeks ago · Laveena (IN) bought 2 weeks ago · Poonam (IN) bought 2 weeks ago · Uday (IN) bought 2 weeks ago
The Fitness Centers database for Uttar Pradesh, India contains 6,288+ verified businesses as of 2026, each with phone, email, address, website and GPS coordinates. The full record count is shown on this page above.
The complete Fitness Centers database for Uttar Pradesh, India is available on this page from Data2Sales AI as an instant CSV download. Every record carries verified contact details and is delivered immediately after checkout.
Each record includes: Business name, Street address, City, State / Region, Postal code, Country, Phone number, Email address and more. The file is delivered as a UTF-8 CSV that opens in Excel, Google Sheets or any standard CRM importer.
Every record is cross-referenced across public business registries, Google Maps and licensed directory partners before it ships. Closed businesses, disconnected phones and duplicates are stripped on every monthly refresh, so the dataset reflects the live fitness centers footprint in Uttar Pradesh, India.
Yes. The Fitness Centers dataset is rebuilt on a rolling 30-day cycle. New entrants come in through registrar filings; closures are detected from negative signals and dropped before export.
Yes — the dataset is licensed for commercial use after purchase. Common use cases include cold outbound, geo-targeted advertising, market research, supplier sourcing and territory planning. Only publicly listed business contact information is included.
You receive a UTF-8 encoded CSV. It opens in Excel, Google Sheets, Power BI, Looker Studio and every major CRM (HubSpot, Salesforce, Zoho, Pipedrive). XLSX is available on request.
Within 30 seconds of successful payment. The CSV is generated fresh from the live database at purchase time. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
The World Wide Data Database for Uttar Pradesh, India is a 6,288+ verified records directory of world wide data businesses — aggregated through the Data2Sales AI engine, cross-referenced across public business registries, official company websites, licensed directory partners, and social platforms, then re-verified monthly so every record in the export is deliverable on day one.
Last Update:
Jul 06, 2026 04:20 AM
Published:
May 11, 2026 02:28 AM
Rows (Regular):
2,830
Rows (Extended):
6,288
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
