Zimbabwe Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 23 March 2026.
Here you’ll find a curated sample of 100 key cities from Zimbabwe, each with essential data points such as latitude, longitude, administrative region, and other relevant attributes.
This preview is extracted from our full dataset, which includes a total of 1773 geographic locations across Zimbabwe.
Whether you’re working on mapping, analytics, or app development, the data is available for both personal and commercial use.
All entries can be downloaded in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML.
Capital Highlight: The official capital city of Zimbabwe is Harare.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 880956 | Sinyoni | ZW | Matabeleland South | -22.2 | 30.35 | 0 | Africa/Harare | populated place | |||
| 7507299 | Mawindo | ZW | Masvingo | -19.81605 | 31.72783 | 0 | Africa/Harare | populated place | |||
| 7393914 | Chief Chilimanzi | ZW | Midlands | -19.5357 | 30.65269 | 0 | Africa/Harare | populated place | |||
| 7351881 | Mugando | Mugando | ZW | Mashonaland Central | -16.94772 | 31.51187 | 0 | Africa/Harare | populated place | ||
| 887346 | Manjelengwa | ZW | Matabeleland North | -19.26758 | 27.37096 | 0 | Africa/Harare | populated place | |||
| 7507377 | Tangano | ZW | Masvingo | -19.90515 | 31.79851 | 0 | Africa/Harare | populated place | |||
| 7507022 | Chindito | ZW | Masvingo | -19.70264 | 31.71052 | 0 | Africa/Harare | populated place | |||
| 7370631 | Mapungantsi | Mapungantsi | ZW | Mashonaland West | -16.55521 | 29.84925 | 0 | Africa/Harare | populated place | ||
| 884995 | Mutambara | ZW | Manicaland | -19.55298 | 32.65634 | 0 | Africa/Harare | populated place | |||
| 7507043 | Mapfumo | ZW | Masvingo | -19.7217 | 31.74149 | 0 | Africa/Harare | populated place | |||
| 7507420 | Maperezano | ZW | Masvingo | -19.93168 | 31.87936 | 0 | Africa/Harare | populated place | |||
| 7453427 | Chirimudombo | ZW | Manicaland | -19.36052 | 31.92208 | 0 | Africa/Harare | populated place | |||
| 887563 | Malila | ZW | Matabeleland North | -19.1896 | 27.67798 | 0 | Africa/Harare | populated place | |||
| 892075 | Duchess Hill | ZW | Mashonaland West | -18.3 | 30.21667 | 0 | Africa/Harare | populated place | |||
| 7523394 | Kenmaur | ZW | Matabeleland North | -19.10376 | 27.97545 | 0 | Africa/Harare | populated place | |||
| 882125 | Rupepwe | ZW | Midlands | -19.73333 | 30.66667 | 0 | Africa/Harare | populated place | |||
| 879360 | Vozheka | Vozheka,Vozueka | ZW | Matabeleland North | -19.12991 | 27.52263 | 0 | Africa/Harare | populated place | ||
| 7507039 | Mangwiro | ZW | Masvingo | -19.76443 | 31.81741 | 0 | Africa/Harare | populated place | |||
| 7319097 | Koodoovale | Koodoovale | ZW | Matabeleland South | -20.98518 | 29.04089 | 0 | Africa/Harare | populated place | ||
| 894625 | Butabubili | Butabubili,Butabulili | ZW | Matabeleland North | -19.76067 | 27.2233 | 0 | Africa/Harare | populated place | ||
| 7464987 | Mpandamanzi | ZW | Matabeleland North | -19.40226 | 27.48233 | 0 | Africa/Harare | populated place | |||
| 882365 | Rocky Spruit | Rocky Spruit | ZW | Mashonaland East | -18.31667 | 31.13333 | 0 | Africa/Harare | populated place | ||
| 8304065 | Masenda | ZW | Manicaland | -19.45471 | 31.82885 | 0 | Africa/Harare | populated place | |||
| 886623 | Matopos | Matobo,Matombo,Matopos | ZW | Matabeleland South | -20.40885 | 28.4778 | 0 | Africa/Harare | populated place | ||
| 7453771 | Magombedze | ZW | Masvingo | -19.48616 | 31.62491 | 0 | Africa/Harare | populated place | |||
| 894809 | Brawlands | ZW | Mashonaland Central | -17.38333 | 31.03333 | 0 | Africa/Harare | populated place | |||
| 7453478 | Chief Nyashanu | ZW | Manicaland | -19.39753 | 31.70671 | 0 | Africa/Harare | populated place | |||
| 7453751 | Gudo | ZW | Masvingo | -19.49378 | 31.54867 | 0 | Africa/Harare | populated place | |||
| 7507025 | Ruzive | ZW | Masvingo | -19.70396 | 31.74312 | 0 | Africa/Harare | populated place | |||
| 7507268 | Jani | ZW | Masvingo | -19.95201 | 31.60871 | 0 | Africa/Harare | populated place | |||
| 7453799 | Panganai | ZW | Masvingo | -19.56303 | 31.62808 | 0 | Africa/Harare | populated place | |||
| 7405323 | Mugaba | ZW | Mashonaland West | -18.24377 | 30.46945 | 0 | Africa/Harare | populated place | |||
| 886049 | Mkauzaan | Mkauzaan,Nkanzaan | ZW | Matabeleland North | -19.56316 | 27.07239 | 0 | Africa/Harare | populated place | ||
| 894903 | Bonke | Banke,Bonke | ZW | Matabeleland North | -19.31667 | 27.37356 | 0 | Africa/Harare | populated place | ||
| 7507046 | Mugwagwa | ZW | Masvingo | -19.71249 | 31.6913 | 0 | Africa/Harare | populated place | |||
| 878564 | Zuzumba | ZW | Matabeleland North | -20.03333 | 27.93333 | 0 | Africa/Harare | populated place | |||
| 7371126 | Nyahuma | Nyahuma | ZW | Mashonaland West | -16.88372 | 29.3764 | 0 | Africa/Harare | populated place | ||
| 887616 | Makwiro | Makwino,Makwira,Makwiro | ZW | Mashonaland West | -17.96667 | 30.43333 | 0 | Africa/Harare | populated place | ||
| 7371172 | Nbewedzebonde | Nbewedzebonde | ZW | Mashonaland West | -16.94507 | 29.33267 | 0 | Africa/Harare | populated place | ||
| 894020 | Chief Madliwa | Chief Madhliwa,Chief Madliwa | ZW | Matabeleland North | -18.7373 | 28.81655 | 0 | Africa/Harare | populated place | ||
| 894280 | Chatsworth | Chatsworth | ZW | Masvingo | -19.6266 | 30.83749 | 0 | Africa/Harare | populated place | ||
| 7507027 | Sonono | ZW | Masvingo | -19.69184 | 31.71004 | 0 | Africa/Harare | populated place | |||
| 7405352 | Nyandebvu | ZW | Mashonaland West | -18.18368 | 30.63743 | 0 | Africa/Harare | populated place | |||
| 7351836 | Muserepu | Muserepu | ZW | Mashonaland Central | -16.92559 | 31.56359 | 0 | Africa/Harare | populated place | ||
| 7507451 | Mandivengereyi | ZW | Masvingo | -19.89785 | 31.9772 | 0 | Africa/Harare | populated place | |||
| 882100 | Rusape | Rusape,Rusapi | ZW | Manicaland | -18.52785 | 32.12843 | 29292 | Africa/Harare | populated place | ||
| 8304096 | Muchuchu | ZW | Manicaland | -19.50251 | 31.88269 | 0 | Africa/Harare | populated place | |||
| 7405705 | Tichavaka | ZW | Mashonaland East | -18.81126 | 31.48587 | 0 | Africa/Harare | populated place | |||
| 7443462 | Chitando | ZW | Manicaland | -19.07542 | 31.73442 | 0 | Africa/Harare | populated place | |||
| 887638 | Makvlela | ZW | Matabeleland South | -19.93333 | 27.23333 | 0 | Africa/Harare | populated place | |||
| 7370758 | Nyikadzino | Nyikadzino | ZW | Mashonaland West | -16.70966 | 29.24552 | 0 | Africa/Harare | populated place | ||
| 7453831 | Chifadza | ZW | Manicaland | -19.47043 | 31.80201 | 0 | Africa/Harare | populated place | |||
| 7351834 | Manyika | Manyika | ZW | Mashonaland Central | -16.92246 | 31.53965 | 0 | Africa/Harare | populated place | ||
| 884328 | Ngulalikashi | ZW | Matabeleland North | -19.7 | 27.08333 | 0 | Africa/Harare | populated place | |||
| 886930 | Maryland Junction | Maryland,Maryland Junction | ZW | Mashonaland West | -17.65 | 30.48333 | 0 | Africa/Harare | populated place | ||
| 7323951 | Chief Chisunga | Chief Chisunga | ZW | Mashonaland Central | -16.05267 | 30.35748 | 0 | Africa/Harare | populated place | ||
| 7464967 | Bonyonko | ZW | Matabeleland North | -19.32295 | 27.62657 | 0 | Africa/Harare | populated place | |||
| 7464994 | Maqetuka | ZW | Matabeleland North | -19.52964 | 27.603 | 0 | Africa/Harare | populated place | |||
| 888077 | Machihiri | ZW | Midlands | -17.33333 | 28.93333 | 0 | Africa/Harare | populated place | |||
| 894010 | Chief Sinasenkwe | Chief Sinasenkwe | ZW | Matabeleland North | -17.53971 | 27.90337 | 0 | Africa/Harare | populated place | ||
| 891758 | Empress Mine | Empress Mine,Empress Mine Township | ZW | Midlands | -18.4577 | 29.44266 | 0 | Africa/Harare | populated place | ||
| 7453092 | Madya | ZW | Manicaland | -19.16976 | 31.76039 | 0 | Africa/Harare | populated place | |||
| 8300461 | Mukwakwe | Mukwakwe | ZW | Midlands | -20.55355 | 30.33827 | 0 | Africa/Harare | populated place | ||
| 879656 | Umsweswe | Sweswe,Umsweswe,Umsweswe Siding | ZW | Mashonaland West | -18.45 | 29.81667 | 0 | Africa/Harare | populated place | ||
| 7507256 | Mukoriro | ZW | Masvingo | -19.92326 | 31.59044 | 0 | Africa/Harare | populated place | |||
| 895326 | Bauhinia | ZW | Mashonaland Central | -17.36667 | 31.03333 | 0 | Africa/Harare | populated place | |||
| 881919 | Sadza | ZW | Mashonaland East | -18.9 | 31.28333 | 0 | Africa/Harare | populated place | |||
| 892706 | Daisyfield | ZW | Midlands | -19.71667 | 29.5 | 0 | Africa/Harare | populated place | |||
| 7507010 | Chiwara | ZW | Masvingo | -19.6272 | 31.73831 | 0 | Africa/Harare | populated place | |||
| 889014 | Kenilworth Estates | ZW | Matabeleland North | -19.43333 | 28.95 | 0 | Africa/Harare | populated place | |||
| 889279 | Kanyemba | Kanyemba | ZW | Mashonaland Central | -15.7 | 30.31667 | 0 | Africa/Harare | populated place | ||
| 7507302 | Mari | ZW | Masvingo | -19.84162 | 31.67859 | 0 | Africa/Harare | populated place | |||
| 11523382 | Bexley Circle | ZW | Mashonaland East | -17.86791 | 31.01073 | 0 | Africa/Harare | populated place | |||
| 7465065 | Nkomombili | ZW | Matabeleland North | -19.97135 | 27.65626 | 0 | Africa/Harare | populated place | |||
| 7507117 | Gogode | ZW | Masvingo | -19.67755 | 31.55598 | 0 | Africa/Harare | populated place | |||
| 7507331 | Chigavade | ZW | Masvingo | -19.92405 | 31.71703 | 0 | Africa/Harare | populated place | |||
| 8304251 | Dungu | ZW | Masvingo | -19.89515 | 31.59012 | 0 | Africa/Harare | populated place | |||
| 880815 | Somqibe | Somqibe,Somquibe | ZW | Matabeleland North | -19.69181 | 27.68639 | 0 | Africa/Harare | populated place | ||
| 7453773 | Tizeyi | ZW | Masvingo | -19.50776 | 31.64683 | 0 | Africa/Harare | populated place | |||
| 7507300 | Nemashakwe | ZW | Masvingo | -19.82939 | 31.67542 | 0 | Africa/Harare | populated place | |||
| 7446880 | Makamure | ZW | Manicaland | -19.165 | 31.70996 | 0 | Africa/Harare | populated place | |||
| 888204 | Lusulu | Lusulu,Lusulu Settlement | ZW | Matabeleland North | -18.06378 | 27.83478 | 0 | Africa/Harare | populated place | ||
| 887202 | Mapengula | Mapengula,Sibanjiba | ZW | Matabeleland North | -19.36361 | 27.42956 | 0 | Africa/Harare | populated place | ||
| 7453889 | Musungwa | ZW | Masvingo | -19.61878 | 31.76007 | 0 | Africa/Harare | populated place | |||
| 7405725 | Tanyanyiwa | ZW | Mashonaland East | -18.82079 | 31.04169 | 0 | Africa/Harare | populated place | |||
| 880906 | Siwila | Siwila,Siwile | ZW | Matabeleland North | -19.73015 | 27.71868 | 0 | Africa/Harare | populated place | ||
| 7465006 | Madziba | ZW | Matabeleland North | -19.6503 | 27.74051 | 0 | Africa/Harare | populated place | |||
| 7464937 | Emapanini | ZW | Matabeleland North | -19.10716 | 27.66174 | 0 | Africa/Harare | populated place | |||
| 893337 | Chiso | ZW | Masvingo | -20.55 | 31.31667 | 0 | Africa/Harare | populated place | |||
| 881643 | Sanyatwe | Sanyatwe | ZW | Manicaland | -18.36119 | 32.59968 | 0 | Africa/Harare | populated place | ||
| 7507362 | Mhazvo | ZW | Masvingo | -19.88435 | 31.76214 | 0 | Africa/Harare | populated place | |||
| 7454323 | Tafirenyika | ZW | Masvingo | -19.71265 | 31.87046 | 0 | Africa/Harare | populated place | |||
| 7506507 | Gwatemba | Gwatemba | ZW | Matabeleland South | -20.40075 | 29.67381 | 0 | Africa/Harare | populated place | ||
| 7507416 | Makinhiwa | ZW | Masvingo | -19.91294 | 31.85553 | 0 | Africa/Harare | populated place | |||
| 895227 | Bemba | ZW | Matabeleland North | -19.44551 | 27.27852 | 0 | Africa/Harare | populated place | |||
| 7453093 | Chinzou | ZW | Manicaland | -19.19057 | 31.74483 | 0 | Africa/Harare | populated place | |||
| 879934 | Tshefu Tshefu | ZW | Matabeleland North | -19.16101 | 27.57644 | 0 | Africa/Harare | populated place | |||
| 887831 | Majabani | Majabani,Zemandana | ZW | Matabeleland North | -19.43333 | 27.5 | 0 | Africa/Harare | populated place | ||
| 7507419 | Rwauya | ZW | Masvingo | -19.92882 | 31.89635 | 0 | Africa/Harare | populated place | |||
| 7465017 | Mbute | ZW | Matabeleland North | -19.77606 | 27.74104 | 0 | Africa/Harare | populated place |
Zimbabwe Unfolded: A Geographic Tapestry Ready for Precision Mapping
A Country of Contrasts and Continuity
There is something deeply magnetic about Zimbabwe. From the ancient city ruins of Great Zimbabwe to the bold geometry of Harare’s expanding suburbs, the country pulses with historical depth and geographic complexity. It is a land defined by plateaus, watersheds, escarpments, and cultural transitions—all intricately layered across provincial boundaries and administrative divisions. As a geographer, I can’t look at Zimbabwe without feeling the urge to map, organize, and understand it at a cellular level.
Mapping Zimbabwe properly means more than just placing dots on a map. It means revealing the logic behind settlement patterns, connecting cities to their regional authorities, and linking localities through precise geographic coordinates. That’s exactly what our urban dataset accomplishes—with a level of detail and usability I’ve long dreamed of making accessible.
Urban Data Rooted in Administrative Logic
You cannot work with Zimbabwe’s urban landscape without acknowledging its structure. Every city or town is nested in a province, further subdivided by departments that affect its governance and services. Whether you're looking at Gweru in the Midlands or Mutare near the Mozambican border, the relevance of administrative alignment is critical.
Our dataset connects each city to its proper province and department with rigorous consistency. This isn’t superficial tagging—it’s an integrated framework that respects the country's spatial governance.
Latitude and Longitude Anchored in Accuracy
We’ve taken care to ensure that every city and town listed includes its precise latitude and longitude—no estimations, no placeholders. From border towns like Plumtree to remote settlements tucked along the Zambezi, each urban center has its coordinates documented and verified.
This allows for seamless integration with GIS systems, mapping software, logistics platforms, or academic models. If you're doing real spatial work in Zimbabwe, you need real spatial data.
The Excel (.xlsx) Breakthrough
For a long time, I heard the same request again and again: “Can I get it in Excel?” I’m thrilled to say—yes, you can now obtain the Zimbabwe city dataset in Excel (.xlsx) format. And not just a raw export, but a carefully structured, fully navigable spreadsheet that lets you sort, filter, and analyze with the fluidity that only Excel delivers.
Excel makes the data practical. Whether you’re comparing city growth across provinces, preparing presentations for NGOs, or planning rural outreach programs, the Excel version turns geographic theory into actionable insight.
All Five Formats, One Comprehensive Dataset
While Excel takes center stage in this latest update, our commitment to multi-format accessibility remains. The Zimbabwe dataset is available in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML. Each format is clean, standardized, and ready for deployment across a variety of digital environments.
Whether you’re building a web-based map, populating a relational database, or simply reviewing city-region relationships in a spreadsheet, you’re fully equipped.
Why Zimbabwe Needs Fresh Cartography
Zimbabwe’s urban dynamics are evolving. New mining towns emerge, infrastructure corridors shift, and internal migration reshapes population density. Relying on outdated data is not just inefficient—it’s misleading. Our dataset was built to reflect the living geography of Zimbabwe: detailed, organized, and responsive to the country’s rhythms.
Empowering Geographers, Developers, and Decision-Makers
This project wasn’t just made for fellow geographers (though they’ll love it). It’s for developers building tools, planners coordinating regional strategies, educators teaching spatial literacy, and humanitarian workers assessing access routes. By providing city data with administrative layers and geolocation precision—and especially with Excel now available—we’ve turned Zimbabwe’s geography into a tool for impact.
Conclusion: Zimbabwe, Structured and Mapped with Purpose
To understand Zimbabwe is to respect its structure: cities rooted in history, governed by regional complexity, and scattered across a richly textured landscape. With our latest release—including full Excel support—this data is finally accessible in a format that speaks to both passion and practicality. Dive into Zimbabwe, not as a distant observer, but as someone equipped to read its geography with clarity and intent.
