How to Remove Duplicate and Permanently Closed Places from a Google Maps Export (2026)

Old saved lists collect debris. A restaurant closes, a hotel is saved twice, a business moves, or two people add the same place under slightly different names. Exporting everything faithfully can preserve the mess just as faithfully.

A clean export has two separate problems:

• permanently closed places, which ExportMyMap can filter before download;
• duplicates, which need evidence and a human decision.

There is no safe universal “remove duplicates” button. Two Starbucks locations share a name but are not duplicates. Two pins at the same building may represent different entrances. And two records for the same restaurant may carry different notes worth merging.

What this process changes

Cleaning an export does not edit the original Google Maps list. Hiding a closed place, deselecting a row, or deleting it in Excel affects only the file you create.

That separation is useful. You can produce a clean client file without destroying the historical source. If you later decide to clean Google Maps itself, use the exported Google Maps URLs to open and remove confirmed entries one by one.

Part 1: Exclude permanently closed places before export

Open the list on a computer in Chrome, Edge, Brave, or Arc and install the ExportMyMap extension.

1. Scan the saved list.
2. Load the detailed place filters and wait for enrichment to finish.
3. If the scan finds at least one closed entry, Hide permanently closed appears.
4. Turn it on and check the new visible and selected count.

If the switch does not appear after enrichment finishes, Google returned no places marked permanently closed in that scan. Continue with the duplicate review instead of looking for a hidden control.

ExportMyMap obtains closure status while loading the available place details. When the filter is active, closed places disappear from the current filtered selection and are omitted from the export.

This works well when the goal is a current travel list, sales territory, supplier sheet, KML, GPX, or PDF. If the goal is an audit—“which of our saved locations have closed?”—do not throw that information away. Export JSON, which retains the permanentlyClosed field, or create a PDF for review before producing the clean copy.

Closure status is still data supplied by Google, not a legal fact. Verify important venues directly, especially when a move, seasonal closure, or duplicate business listing might look like a permanent shutdown.

Part 2: Export a working spreadsheet

Choose Excel or CSV for duplicate analysis. The useful columns include:

• name;
• fullAddress;
• latitude and longitude;
• placeId;
• googleMapsUrl;
• dateAdded and dateUpdated when available;
• note, if notes are included.

Excel is easier for manual review. CSV is convenient for a database or script. The Excel and Google Sheets export guide covers opening and sorting the file safely.

Save the untouched download before editing. Then work on a copy named something explicit, such as:

lisbon-restaurants-cleaning-copy-2026-07.xlsx

Part 3: Find exact duplicates first

Start with the strongest identifiers.

1. Place ID

A non-empty Place ID identifies a Google place record. Sort by placeId or use spreadsheet duplicate highlighting on that column.

Do not run “Remove Duplicates” blindly on the entire column while blank cells are included. Blank does not mean that every row refers to the same unknown place. Filter to non-empty IDs first, inspect each repeated group, and keep one confirmed record.

2. Google Maps URL

Repeated googleMapsUrl values are strong duplicate candidates. URLs can contain tracking or presentation differences, so identical URLs are more useful than merely similar-looking ones.

3. Coordinates plus identity

When Place ID and URL are absent, compare latitude, longitude, name, and address together.

Coordinates alone are not always enough. A shopping center, station, or office building can contain several legitimate places at one point. Names alone are worse: chains deliberately reuse them.

A likely duplicate has nearly identical coordinates and a matching normalized name or address.

Part 4: Review near-duplicates

The difficult cases are not identical rows:

• “Joe's Pizza” and “Joe’s Pizza – Downtown”;
• an old business listing and its replacement;
• the same attraction saved through two Google place records;
• a moved business with the old and new address;
• one place saved with a note and another without.

Sort by address, then by name. Look at small groups rather than the whole spreadsheet. Open both Google Maps URLs and ask:

1. Are the pins at the same physical place?
2. Do they represent the same current business or two units?
3. Is one record permanently closed?
4. Does either row contain a note, date, or URL that should be kept?
5. Would deleting one remove useful history?

Keep the row with the most stable identity and complete data. Copy any useful personal note before deleting the other. The notes preservation guide explains why this matters across formats.

Part 5: Clean map files and PDFs

Deleting a row in Excel does not automatically rewrite the GPX or KML that ExportMyMap created. If the final deliverable is a map file or PDF:

1. Use the spreadsheet to identify confirmed duplicate names and addresses.
2. Return to the scanned list in ExportMyMap.
3. Search for each duplicate.
4. Deselect the extra record.
5. Keep Hide permanently closed enabled.
6. Export KML, GPX, GeoJSON, PDF, Print, or a share link from the cleaned selection.

This second pass is slower than a magic button, but it prevents a spreadsheet guess from silently deleting the wrong map point.

For migration, clean before importing. Otherwise MAPS.ME, Locus Map, or Gaia GPS will receive the duplicates and you will have to remove them in a less convenient mobile interface.

A sensible order of operations

Use this order:

1. preserve the untouched original export;
2. decide whether notes belong in the working copy;
3. exclude confirmed permanently closed places;
4. identify exact duplicates by stable fields;
5. review near-duplicates manually;
6. merge useful notes;
7. produce the clean destination file;
8. compare counts and spot-check the result.

Removing notes or closure history too early makes duplicate decisions harder. Cleaning first and archiving later risks losing the evidence you needed.

Common mistakes

Removing every repeated name. Chain locations and common attraction names are not duplicates.

Treating blank Place IDs as one duplicate group. Blank means the identifier is unavailable, not that the places are identical.

Using rounded coordinates alone. Several businesses can share a building or map pin.

Deleting both rows. Spreadsheet filtering can hide the row you meant to keep. Recheck the group before deletion.

Assuming “permanently closed” means useless. Historical research, expense records, inspections, and memories may need the closed entry. Produce a current copy without destroying the archive.

Cleaning only the spreadsheet. The separately downloaded KML, GPX, or PDF still contains the original selection unless you create it again.

Verify the clean result

Count the final rows or waypoints and compare them with:

original places − excluded closed places − confirmed duplicate extras

Then spot-check:

• one retained duplicate group;
• one place near another with the same name;
• one place with a merged note;
• the first and last entry;
• a remote pin.

For a PDF, open the first, middle, and final pages. For KML or GPX, use the corresponding validator and confirm the expected number of points.

The result should be a clean working copy, not an irreversible rewrite of your only source.

Export and clean your Google Maps saved places →