Plot Multiple Addresses on a Map

How to plot multiple addresses on a map

Putting a list of addresses on one map is one of the most common mapping jobs, and it usually starts in a spreadsheet: a list of customers, job sites, store branches, open houses or volunteer homes. Paid tools such as Maptive, BatchGeo or EasyMapMaker do this behind a sign-up form. This page does it for free, in your browser, for up to 200 addresses at a time.

1. Paste or upload your list. Put one address per line in the box, or upload a CSV file exported from Excel, Google Sheets or your CRM. A header row is optional for plain lists and required for CSV files with extra columns.
2. Press “Geocode & plot”. Each address is turned into latitude and longitude (this step is called geocoding). The progress bar shows how many rows are done. You can cancel at any time and continue later.
3. Check the results. Pins appear on the map as they are found and the map zooms to fit all of them. The table lists every row with its coordinates and how precise the match is. Rows that did not match are highlighted, with Edit and Retry buttons.
4. Download. Save the results as CSV (to put the coordinates back into your spreadsheet), GeoJSON (for web maps and GIS software) or KML (for Google Earth and Google My Maps).

Click any pin to see its label, the address you typed, its category and its coordinates. Clicking a row in the results table flies the map to that pin, which is the quickest way to check a suspicious match.

If your spreadsheet already has latitude and longitude columns you don't need geocoding at all: use the CSV to map tool, which plots coordinates directly and has no row-by-row lookups. For a single address, the address to coordinates converter shows several candidate matches so you can pick the right one.

Supported formats: address lists, CSV and spreadsheets

The tool reads three shapes of input and works out which one you pasted from the first line.

1. A plain list, one address per line

The simplest input. Anything that does not look like a CSV header is treated as an address list. Blank lines are skipped.

2. A CSV with a single address column

If the first line contains a column called address (or full address, street address or location), the file is read as CSV. Two optional columns are recognized: a label (label, name, title, store, customer or company) and a category (category, type, group, segment or status). Other columns are ignored. Wrap any value that contains a comma in double quotes, which Excel and Google Sheets do automatically when they export CSV.

3. A CSV with separate street, city, state and ZIP columns

Many CRM and mailing-list exports split the address into parts. If the header has street (or address1), city, state and zip columns, they are joined into one address before geocoding. A country column is added if present. ZIP codes that lost their leading zero in Excel (a Boston ZIP 02108 saved as 2108) are padded back to five digits.

Tab-separated text (what you get when you copy cells straight out of a spreadsheet) and semicolon-separated files (common in Europe) are detected too. Files should be UTF-8; if accented characters look garbled, re-export from your spreadsheet as “CSV UTF-8”.

Colors, labels and categories

Every distinct value in the category column gets its own pin color, assigned in the order the values first appear. The palette starts with the Okabe–Ito colors, which stay distinguishable for people with the most common forms of color blindness. A legend under the map shows each category with its count of plotted pins. Rows with an empty category are grouped as “Uncategorized”.

Up to ten categories get distinct colors; after that the colors repeat, so if you have dozens of categories, consider grouping them (for example by region or by sales tier) before plotting. The label column is used as the pin's popup title and as the placemark name in the KML export. Without a label, the address itself is used.

If you need a polished, presentation-ready map with a custom legend title, export the GeoJSON and open it in the map with legend maker, or add pins by hand with the pin drop map.

Examples of mapping multiple locations

Sales territory review

A regional manager exports 180 active accounts from a CRM with columns company, street, city, state, zip, rep. Renaming rep to category colors each pin by sales rep. Overlaps between reps, and gaps where no one is covering an area, are obvious within seconds. The CSV export then carries latitude and longitude back into the CRM for future use.

Open-house or service-call day

A real-estate agent pastes eight listing addresses, one per line, to see which ones cluster together. To put them in a sensible driving order, copy the coordinates into the multi-stop route distance tool, or compare every pair at once with the distance matrix calculator.

Store locations for a website

A retailer maps 40 branches with a type column (Store, Outlet, Pickup point), checks every pin, and downloads GeoJSON for its store-locator widget. Because the coordinates come from OpenStreetMap, the data can be reused with attribution under the ODbL.

Event and volunteer planning

A nonprofit maps volunteer home ZIP codes and addresses to choose a central meeting place. Once the pins are plotted, the geographic center finder gives the balance point of the group, and the radius map tool shows who lives within 10 or 25 miles of it.

Exporting your map: CSV, GeoJSON and KML

• CSV contains every row, matched or not, with the columns row, label, category, input_address, status, latitude, longitude, matched_address. Coordinates have six decimals (about 10 cm of resolution, far finer than the geocoding itself). Open it in Excel or Google Sheets and look up the row number to join it back to your original sheet.
• GeoJSON is a FeatureCollection of Point features in WGS84 longitude/latitude order, as RFC 7946 requires. Only matched rows are included. It loads directly into QGIS, Mapbox, Leaflet, MapLibre, ArcGIS Online and our GeoJSON viewer.
• KML creates one placemark per matched address with a colored icon per category. Import it into Google Earth, or into Google My Maps via “Import” on a layer. You can preview it in the KML viewer.

The “copy” button in the result headline copies the same CSV text to your clipboard, which is handy for pasting straight into a spreadsheet without saving a file.

Accuracy and geocoding limits

Geocoding is a lookup against a database of known addresses, streets and places. This tool uses Photon, a free geocoder built on OpenStreetMap data. It is good at well-formed street addresses in towns and cities, and at named places. It is weaker where OpenStreetMap has not mapped house numbers, which is common in rural areas and some suburbs. In those cases it falls back to the street, the ZIP code or the town, and the Match column tells you which happened.

The error ranges above are typical figures, not guarantees. A pin can land on the right street but the wrong block when a house number is interpolated, or on the right building's centroid rather than its entrance. For anything where a few meters matter (property lines, emergency dispatch, utility work), verify each point against an authoritative source such as a county parcel map.

Why the 200-row limit and the pause between lookups?

Photon is a free public service run by komoot. Its fair-use policy asks clients not to flood it with parallel requests, so this tool sends one request at a time with a short pause (about a third of a second) between them. That keeps a 200-row batch to roughly two minutes. For thousands of addresses, split the list into batches of 200, or use a commercial geocoder with a bulk API and a service agreement.

Privacy

Your file is read in the browser. The only thing that leaves your device is each address string, sent to the Photon geocoder to be looked up. Labels, categories and other columns are never sent. Don't include personal names inside the address field if that matters to you; keep them in the label column instead.

Fixing addresses that do not match

When a row shows “No match”, click Edit, correct the text and press Enter. The most common fixes are:

• Add the city and state. “100 Main St” exists in thousands of towns. Without a city the geocoder picks one at random or fails.
• Remove suite, unit and floor numbers. “Suite 400”, “Apt 3B” or “Floor 2” often confuse the match and don't change the building location anyway.
• Drop PO boxes. A PO box is at the post office, not at the customer, so it can't be plotted meaningfully. Use the physical address if you have it.
• Spell out or simplify unusual abbreviations. Standard ones (St, Ave, Rd, NW) are fine; internal codes, building nicknames or “c/o” lines are not.
• Try the ZIP code alone if you only need a rough location: “83702, USA” plots the center of the ZIP area.

Retry re-sends the address without using the cached answer, which helps after a temporary network error. If a pin is matched but lands in the wrong place (for example, a same-named street in another state), add the state or ZIP code to that line of your list and plot again, or check the candidates one by one in the address to coordinates tool.

Other ways to map multiple locations

This tool is built for one job: turning a list of addresses into pins and coordinates quickly, without an account. Depending on what you need next, another approach may suit you better:

• Google My Maps can import a spreadsheet and geocode it with Google's data, which has better house-number coverage in some rural areas. It needs a Google account, and the map lives in your Google Drive.
• Desktop GIS such as QGIS can geocode with plugins and style thousands of points, but takes time to learn. Our GeoJSON export opens in QGIS directly, so you can start here and continue there.
• Paid batch geocoders (commercial address APIs) handle tens of thousands of rows, return a match-quality score per row, and come with service agreements. They make sense for recurring jobs or for data you must be able to audit.
• Coordinates you already have need no geocoding: paste them into the CSV to map tool, or drop pins by hand on the pin drop map when there are only a few.

A practical workflow for a list of a few hundred addresses is: plot it here, fix the unmatched rows, export CSV, and keep the latitude and longitude columns in your master spreadsheet. Next time you only need the CSV to map tool, and no lookups are repeated.