County Mapper

Use the new Britain and Ireland Mapper instead
Enter a Surname or SNP
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Map Options



Nothing to see here until you enter a surname or Y-SNP.

notes ↓
These tables show census population by county and percent by country for the selected surname. The value for the top widest bar corresponds to the most saturated color in the map. In some cases the census data is more detailed than the available map coordinates, for example Berwick is a historic county in Scottish Borders, while for most Irish surnames the available census data is at the province level. See the Discussion tab for more details.

For SNPs, surnames with totals in blue are also found among the top 50 names per county in 1881, and so can be mapped. Those in gray are less common and do not contribute to the map.

Nothing to see here until you enter a surname or Y-SNP.

title notes ↓
Outermost Surnames notes ↓
A center point can be calculated for any surname as the weighted average of its frequency by county. These are the surnames prevalent in the outermost counties of the British Isles.

Basic Usage

First, on the Map tab, use the drop-down menu to show some examples. These illustrate some interesting points of history or curious names and show what the tool can do. Explore the Details and Analysis tabs with the examples.

Click "Random Surname" -- now and then you'll see a purely Welsh, Scots, Irish, or Cornish name. Hold down the option key and click Random Surname to get a random Y SNP.

Enter your own surname, or enter 2 or 3 separated by commas. Click the camera to save a high-resolution map to your Downloads folder, or click Share to put a link to this tool (and your chosen surname or SNP) onto your Clipboard which you can paste into an email or text.

Wild Card Searches: You can combine surnames with a wild card search. * matches anything, < denotes the beginning of a name and > the end of a name. Examples: <Mac matches MacDonald, MacKay, and similar. son> matches Jameson, Richardson, and others, and John*son matches Johnson, Johnston, and Johnstone.

Where's My Name?

These maps are based on available data from the 1881 census of Great Britain and the 1901/1911 censuses of Ireland which consists of the top 50 and top 100 surnames in each county or province, respectively, plus a small amount of data for separate Irish counties and Isle of Man. This adds to about 1000 unique surnames, and if you cannot find your name, it must have been below that prevalence threshold a century ago. Try one of the other mapping services listed under Data Sources below.

Try your terminal Y SNP instead, and you might get some hints about more common surnames from your ancestral area. Otherwise, just have fun with the examples.

Dates and Population Mixing

For genealogical purposes, earlier is generally better; ideally we would like census data from a time period matching our ancestors of interest. For those with colonial American ancestry this means the seventeenth century, which is 200-250 years before the census data, and so we cannot really expect the maps here (or at any site using Victorian data) to reflect surname origins with accuracy.

Fortunately this tool has a quantitative measure of mixing, namely similarity to the overall average. Surnames or SNPs with high similarity to the average cannot be considered accurate reflections of long ago. In contrast, surnames or SNPs with low similarity are not mixed. The results are encouraging and consistent: O' and Mac/Mc names proliferate in Ireland and Scotland. Names ending in -son have a bias to the outlines of the Danelaw and probably reflect that Old Norse patronymic form -- still visible in matched pairs (Roberts/Robertson, Harris/Harrison, etc.) despite centuries of mixing.

For SNPs, the summary box (under the Map tab) shows the time when that SNP became "half mixed", in the sense that the surnames with this SNP reflect half of the complete geographical average of "everyone." This date does not reflect migration into the British Isles, but rather the breadth and diversity of the SNP: for many men of European descent (those with R1b-M269), this date will be between 3600 and 4600 years ago and reflects the huge starburst population expansions of that era. Those Neolithic expansions occurred on continental Europe but sowed the seeds of the number and diversity we see today in surnames. Rare or sparse haplogroups (E, I, G, T, C) will have much earlier half-mixed dates.

Men with R1b-M269 and half-mixed dates after 700 and before 3600 years ago are in the "sweet spot" after surnames appeared but before the diversification of the starburst expansions, and we may expect that they may see surnames related both genetically and geographically in that time period. Examples are R-YP274, R-BY470, R-ZZ7_1, R-A11376 where surname similarity may confirm some of the relationships.

Totals vs Percents and The Industrial Revolution

You may choose to see a map based on percents of a surname in each county, or based on its total prevalence in the British Isles. The choice depends on your interest. If your ancestors lived here after about 1850, then choosing Totals will better reflect where they might have lived, but if they lived here before 1800, then choose Percents for a better picture.

The reason is that the new jobs of the Industrial Revolution fueled major country-to-city migrations to the Midlands and London. From 1800 to 1880, England's overall population grew 210%. Manchester grew 470%, London 330%, and agricultural Wiltshire only 40%. For example, try the surname Scott to see migration south, Cooper north, and Harris east to London.

Geographic Similarity

One of the unique features of this tool is that it will find the most "geographically similar" surnames to any given name. Behind the scenes this is all vector math: each surname generates a vector consisting of its prevalence in Anglo-Irish counties, which may have length zero (surname not known), to one (many Isle of Man names), to 91 (all counties, typically for names like Smith and Taylor). As soon as you enter a surname, this tool calculates the county vectors for all other names (about 1000 in the system), and then calculates the cosine similarity ( between each of those and the entered surname.

In non-mathematical terms, geographically similar surnames have a similar pattern of county prevalence. A southwest surname like Tucker will find names with the same pattern. If you're writing that Great Novel and want names for characters that your protagonist would meet everyday, this will help. Look at the surnames most geographically similar to Wilkinson -- all those ending in -son are echoes of the Danelaw.

The Problems with Counties

One of the difficulties in building a unified mapping tool is that different data sources use different conventions to define counties. In particular we have to combine data for counties in the 1881 census (with surname and population data) with data for the boundaries of counties (with tables of latitude and longitude necessary for mapping). The surname and population data are averaged and apportioned as necessary to draw the map.

In the following list the first name is that available for map boundaries, followed by the census counties that it contains:

  • Aberdeenshire: Aberdeen, Kincardine
  • Argyll and Bute: Argyll, Bute
  • Borders: Berwick, Peebles, Roxburgh, Selkirk
  • Bristol: Gloucestershire, Somerset
  • Cambridgeshire: Cambridgeshire, Huntingdonshire
  • Cumbria: Cumberland, Westmorland
  • Dumfries and Galloway: Dumfries, Kircudbright, Wigtown
  • Gwynedd: Caernarfon, Marioneth
  • Highland: Caithness, Ross, Sutherland
  • Merseyside: Cheshire, Lancashire
  • Moray: Banff, Elgin, Nairn
  • Perth and Kinross: Kinross, Perth
  • Powys: Brecknock, Montgomery, Radnor
  • West Midlands: Staffordshire, Warwickshire

The next list is the converse: the first names are census names, followed by those with map coordinates:

  • Cheshire: Cheshire, Merseyside
  • Denbigh: Denbighshire, Wrexham, Conwy
  • Derry: Strabane, Londonderry
  • Durham: Durham, Tyne and Wear
  • Gloucestershire: Gloucestershire, Bristol
  • Hampshire: Hampshire, Isle of Wight
  • Lancashire: Lancashire, Manchester, Merseyside
  • Somerset: Somerset, Bristol
  • Staffordshire: Staffordshire, West Midlands
  • Stirling: Stirling, Falkirk
  • Sussex: East Sussex, West Sussex
  • Warwickshire: Warwickshire, West Midlands
  • Yorkshire: East Yorkshire, West Yorkshire, South Yorkshire, North Yorkshire

An additional complication is that the most complete Irish surname data are available only at the province level. The four historic Irish provinces and the counties each contains are:

  • Connacht: Galway, Leitrim, Mayo, Roscommon, Sligo
  • Leinster: Carlow, Dublin, Kildare, Kilkenny, Laois, Longford, Louth, Meath, Offaly, Westmeath, Wexford, Wicklow
  • Munster: Clare, Cork, Kerry, Limerick, Tipperary, Waterford
  • Ulster: Antrim, Armagh, Down, Fermanagh, Derry, Tyrone (in Northern Ireland today), Cavan, Donegal, Monaghan (in the Republic of Ireland)

How are Y SNPs Mapped?

To my knowledge there are no tools that attempt county-level resolution of Y SNP ancestral location. SNPs were not known in the era when national census-tasking provided location data for surnames, and even today the data for direct association of Y DNA with ancestral county is very sparse (for example ).

However, men who do Y SNP testing at Family Tree DNA (= FTDNA) may optionally enter their surnames, which FTDNA makes accessible in their comprehensive tree of Y SNPs. From historic census data we can associate surnames with counties. All that remains is to make the connection: Y SNP associated surnames associated counties, which this tool does with appropriate weighting and averaging.

We would expect that the SNP map for "Y Adam" (try A-V221) should be evenly colored since this is every man's common paternal ancestor. Yet it does not come out that way because of the random nature of surname tagging: the high variance of small numbers is apparent for small counties. Therefore all SNP maps are flattened by dividing all values by the median county scores seen for A-V221. While such fudge factors should usually be avoided, in this case the flattening makes weak but interesting patterns visible. Try R-L21 with R-U106 for example: the difference between Bell Beaker R-M269 and Anglo-Saxon R-M269 is subtle but consistent.

Our expectation is that SNP localization may work at a regional level (e.g. Scotland vs Wales vs Cornwall/Devon) but may fail for most surnames since Leslie et al (Nature 2015 ) showed that populous central England is well mixed. This tool provides two ways to gauge the validity of any SNP mapping: first, check the number of surnames with map data under the SNP (i.e. surnames in blue bars in the left column under Details). If there is only one such surname (for example Lynch for R-BY4102), then we know that the map is based solely on that surname and the pattern cannot be older than when surnames arose in the 12th-13th centuries. But if there are several such surnames (for example Duncan, Doherty, McKee, Boyle for R-S673), then we can infer a common ancestry for these branches of these names and have more confidence in their co-location.

The second gauge of SNP location validity is the percent geographic similarity to the average of all surnames. As we move up the SNP tree (back in time), at some point we sweep in everyone's ancestry and there cannot be any geographic differentiation. For that purpose this tool uses SNP A-V221 which was formed 133,000 years ago, so that anywhere outside of Africa the geographic distribution for A-V221 is guaranteed to be all-inclusive (and so uninformative). Thus any SNP with similarity approaching 100% of A-V221 is too inclusive and too well mixed to have an interesting map pattern.

SNP patterns are especially interesting if the SNP was formed well after one of the major bottlenecks, specifically after the starburst ~4000 years ago under R-M269. This topic will eventually get more discussion and illustration in one of my Research Reports.

Alternatives and Data Sources

If your surname is not available here you may be able to find it at one of these sources:

  • British surnames:
  • English and Welsh counties by total:
  • Archer software:
  • Isle of Man:
  • Irish provinces:
  • UK surnames:
  • Irish census:
  • Irish surnames:
  • Irish surnames:
  • Map of historic counties:
  • Howard Mathieson's Geography of Surnames
  • ISOGG resources:
  • International:

How about maps for the US, Canada, Italy, Mexico, Finland, China....

Not anytime soon! It's a question of data availability and scale. This tool has data for 91 counties, while the US has 3100 counties -- a scale that a client-side tool cannot accommodate. US state-level data is probably available but uninteresting due to a very high level of mixing and long dissociation in time and geography from the origin of surnames.

Caveats, questions, comments, requests

This tool is entirely free and it comes with no guarantees. You may download the maps and copy the tables freely, though I would appreciate attribution. If you post to blogs or websites, please include a link to this page.

Please tell me about your ideas for improvement and stories where this tool has been of particular interest to you.

Rob Spencer    
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