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This dataset covers 40,764 records spread across 79 cities in Uttar Pradesh, ready for outreach, segmentation and CRM import.
The largest cities by record count are Meerut (5,202), Ghaziabad (4,466), Prayagraj (4,445), Agra (4,301), Lucknow (4,298), Kanpur (3,958), Varanasi (3,945), and Allahabad (3,364).
Additional coverage spans Bareilly (150), Mirzapur (111), Kanpur Nagar (103), Sultanpur (90), Gorakhpur (82), Hardoi (80), Aligarh (80), Hathras (78), Saharanpur (69), Mathura (68), Jhansi (65), Etawah (64) , plus 59 more cities.
| Cities | Total | With mobile | With website |
|---|---|---|---|
| Meerut | 5,202 | 5,202 | 2,879 |
| Ghaziabad | 4,466 | 4,466 | 2,697 |
| Prayagraj | 4,445 | 4,445 | 2,269 |
| Agra | 4,301 | 4,301 | 2,614 |
| Lucknow | 4,298 | 4,298 | 2,719 |
| Kanpur | 3,958 | 3,958 | 2,281 |
| Varanasi | 3,945 | 3,945 | 2,372 |
| Allahabad | 3,364 | 3,364 | 1,746 |
| Bareilly | 150 | 150 | 99 |
| Mirzapur | 111 | 111 | 44 |
| All cities (80) | 40,764 | 40,764 | 23,062 |
| Cities | Total | With mobile | With website |
|---|---|---|---|
| Meerut | 5,202 | 5,202 | 2,879 |
| Ghaziabad | 4,466 | 4,466 | 2,697 |
| Prayagraj | 4,445 | 4,445 | 2,269 |
| Agra | 4,301 | 4,301 | 2,614 |
| Lucknow | 4,298 | 4,298 | 2,719 |
| Kanpur | 3,958 | 3,958 | 2,281 |
| Varanasi | 3,945 | 3,945 | 2,372 |
| Allahabad | 3,364 | 3,364 | 1,746 |
| Bareilly | 150 | 150 | 99 |
| Mirzapur | 111 | 111 | 44 |
| Kanpur Nagar | 103 | 103 | 58 |
| Sultanpur | 90 | 90 | 39 |
| Gorakhpur | 82 | 82 | 55 |
| Hardoi | 80 | 80 | 36 |
| Aligarh | 80 | 80 | 54 |
| Hathras | 78 | 78 | 34 |
| Saharanpur | 69 | 69 | 38 |
| Mathura | 68 | 68 | 38 |
| Jhansi | 65 | 65 | 38 |
| Etawah | 64 | 64 | 30 |
| Gautam Buddha Nagar | 63 | 63 | 47 |
| Deoria | 63 | 63 | 25 |
| Barabanki | 63 | 63 | 31 |
| Hapur | 62 | 62 | 23 |
| Pratapgarh | 61 | 61 | 27 |
| Ghazipur | 60 | 60 | 28 |
| Muzaffarnagar | 60 | 60 | 30 |
| Moradabad | 59 | 59 | 36 |
| Jaunpur | 58 | 58 | 31 |
| Firozabad | 56 | 56 | 20 |
| Sitapur | 54 | 54 | 26 |
| Pilibhit | 53 | 53 | 26 |
| Azamgarh | 51 | 51 | 27 |
| Shahjahanpur | 50 | 50 | 25 |
| Raebareli | 50 | 50 | 28 |
| Mainpuri | 50 | 50 | 19 |
| Amroha | 49 | 49 | 22 |
| Unnao | 47 | 47 | 18 |
| Farrukhabad | 45 | 45 | 22 |
| Ayodhya | 45 | 45 | 25 |
| Bulandshahr | 45 | 45 | 25 |
| Etah | 44 | 44 | 18 |
| Shamli | 43 | 43 | 17 |
| Kushinagar | 42 | 42 | 19 |
| Mau | 42 | 42 | 12 |
| Kannauj | 41 | 41 | 17 |
| Gonda | 41 | 41 | 18 |
| Kanpur Dehat | 39 | 39 | 15 |
| Fatehpur | 39 | 39 | 13 |
| Budaun | 38 | 38 | 16 |
| Bahraich | 38 | 38 | 14 |
| Maharajganj | 38 | 38 | 20 |
| Basti | 37 | 37 | 16 |
| Sant Kabir Nagar | 34 | 34 | 16 |
| Lalitpur | 34 | 34 | 9 |
| Bhadohi | 33 | 33 | 9 |
| Ambedkar Nagar | 33 | 33 | 24 |
| Sonbhadra | 33 | 33 | 19 |
| Rampur | 32 | 32 | 14 |
| Auraiya | 32 | 32 | 8 |
| Baghpat | 31 | 31 | 12 |
| Bijnor | 31 | 31 | 13 |
| Chandauli | 30 | 30 | 15 |
| Kheri | 30 | 30 | 13 |
| Banda | 30 | 30 | 10 |
| Sambhal | 29 | 29 | 12 |
| Kasganj | 28 | 28 | 8 |
| Lakhimpur Kheri | 28 | 28 | 0 |
| Amethi | 22 | 22 | 12 |
| Mahoba | 22 | 22 | 7 |
| Ballia | 22 | 22 | 17 |
| Jalaun | 20 | 20 | 11 |
| Kaushambi | 20 | 20 | 13 |
| Balrampur | 20 | 20 | 11 |
| Shrawasti | 16 | 16 | 2 |
| Chitrakoot | 15 | 15 | 8 |
| Siddharthnagar | 10 | 10 | 6 |
| Hamirpur | 9 | 9 | 3 |
| Shravasti | 7 | 7 | 1 |
| Smaller regions (combined) | 3,425 | 3,425 | 1,852 |
| All cities (80) | 40,764 | 40,764 | 23,062 |
An estimated 37,058 High Schools records are available for Uttar Pradesh, India from our data source. Your file is pulled at purchase and delivered as a CSV with company name, address, city, state, phone, email, website and GPS coordinates, ready for CRM import or BI analysis.
About 37,058 High Schools records are available for Uttar Pradesh, India as of 2026. That is an estimate of what our data source holds for this area, not a count of a file already sitting on a shelf — the records are pulled when you buy, and each carries phone, email, address, website and GPS coordinates where the source provides them.
The complete High Schools 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 high schools footprint in Uttar Pradesh, India.
Yes. The High Schools 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 High Schools database for Uttar Pradesh, India covers an estimated 37,058 available records. The file is built from our data source when you order, then de-duplicated and cleaned before export, so you receive a current list of high schools businesses rather than a snapshot that has been sitting on a shelf.
Last Update:
Aug 19, 2026 17:39 PM
Published:
May 11, 2026 02:28 AM
Records (Regular licence):
~18,529
Records available:
~37,058
State:
Uttar Pradesh
Country:
India
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
