{"id":1009,"date":"2026-10-23T17:31:27","date_gmt":"2026-10-23T17:31:27","guid":{"rendered":"http:\/\/jfdi-blog-us-county-map-from-excel-fips"},"modified":"2026-10-23T17:31:27","modified_gmt":"2026-10-23T17:31:27","slug":"us-county-map-from-excel-fips","status":"publish","type":"post","link":"https:\/\/jfdi.pro\/blog\/us-county-map-from-excel-fips\/","title":{"rendered":"How to map US county data from Excel (FIPS codes explained)"},"content":{"rendered":"\n

To map US county data, you need a column that identifies each county, ideally its five-digit FIPS code, and a column of values. Paste both into the JFDI map maker<\/a> and it draws all of the roughly 3,200 counties and county-equivalents, with state borders on top. It’s free, there’s no account, and your spreadsheet isn’t uploaded.<\/p>\n\n\n\n

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Open the map maker<\/a><\/div>\n<\/div>\n\n\n\n

Most problems with county maps come from the codes, not the map. Here’s how FIPS codes work and how to avoid the usual gaps.<\/p>\n\n\n\n

What a FIPS code is<\/h2>\n\n\n\n

A county FIPS code has five digits: two for the state, then three for the county within it.<\/p>\n\n\n\n

County<\/th>State code<\/th>County code<\/th>FIPS<\/th><\/tr><\/thead>
Autauga County, Alabama<\/td>01<\/td>001<\/td>01001<\/td><\/tr>
Los Angeles County, California<\/td>06<\/td>037<\/td>06037<\/td><\/tr>
Cook County, Illinois<\/td>17<\/td>031<\/td>17031<\/td><\/tr>
Miami-Dade County, Florida<\/td>12<\/td>086<\/td>12086<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Almost every US government dataset (Census Bureau, BLS, CDC, USDA) includes FIPS codes, often in a column called GEOID<\/code>, FIPS<\/code> or county_fips<\/code>. Codes are more reliable than names, because many states share county names: there are dozens of Washington Counties and Jefferson Counties.<\/p>\n\n\n\n

Step by step<\/h2>\n\n\n\n
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  1. Get your data into two columns<\/strong>: the FIPS code (or county name) and the value. Extra columns are fine.<\/li>\n\n\n\n
  2. Paste it into the map maker<\/a><\/strong>, or drop the CSV or Excel file on the page. It recognises county data and switches to the US county map on its own.<\/li>\n\n\n\n
  3. Check the match count<\/strong> under Data. If any rows aren’t matched, press Fix<\/strong> to see why.<\/li>\n\n\n\n
  4. Pick a scale.<\/strong> With 3,000 areas, a smooth gradient often reads better than steps. Turn on Log scale<\/strong> for things like population density that vary a thousandfold.<\/li>\n\n\n\n
  5. Zoom if you need to.<\/strong> If all your data is in one state or a few neighbouring ones, the map zooms in automatically. You can choose the area yourself under Map \u203a Area<\/strong>.<\/li>\n<\/ol>\n\n\n\n
    \"A
    US counties by people per square kilometre, on a log scale. Census Bureau 2019 estimates.<\/figcaption><\/figure>\n\n\n\n

    Mistake 1: Excel drops the leading zero<\/h2>\n\n\n\n

    Open a CSV in Excel and 01001<\/code> becomes 1001<\/code>. Every county in the seven states whose codes start with 0 (Alabama, Alaska, Arizona, Arkansas, California, Colorado and Connecticut) loses a digit. Joins in other tools then quietly fail for those states.<\/p>\n\n\n\n

    The map maker handles four-digit codes, so 1001<\/code> still finds Autauga County. If you need the zeros back for other work, the JFDI file converter<\/a> keeps them when it turns a CSV into an Excel file. There’s a whole post on why Excel loses leading zeros and how to stop it<\/a>.<\/p>\n\n\n\n

    Mistake 2: Connecticut’s counties no longer exist in the data<\/h2>\n\n\n\n

    Connecticut replaced its eight counties with nine planning regions as county-equivalents. The Census Bureau began publishing data for the regions in 2023, starting with population estimates and the 2022 American Community Survey (CTData<\/a>). The new codes run from 09110 to 09190:<\/p>\n\n\n\n

    FIPS<\/th>Planning region<\/th><\/tr><\/thead>
    09110<\/td>Capitol<\/td><\/tr>
    09120<\/td>Greater Bridgeport<\/td><\/tr>
    09130<\/td>Lower Connecticut River Valley<\/td><\/tr>
    09140<\/td>Naugatuck Valley<\/td><\/tr>
    09150<\/td>Northeastern Connecticut<\/td><\/tr>
    09160<\/td>Northwest Hills<\/td><\/tr>
    09170<\/td>South Central Connecticut<\/td><\/tr>
    09180<\/td>Southeastern Connecticut<\/td><\/tr>
    09190<\/td>Western Connecticut<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

    The region boundaries don’t line up with the old counties, so there’s no honest way to draw old-county data (such as Fairfield County, 09001) on the current map. The map maker tells you this rather than guessing. If your data is older, you’ll need a pre-2022 boundary file, which you can load under Map \u203a Use my own boundaries<\/strong>.<\/p>\n\n\n\n

    Mistake 3: Names that changed<\/h2>\n\n\n\n

    A few counties have been renamed or split, and older datasets still use the old versions:<\/p>\n\n\n\n