CSV to Map

Paste, upload, or drag-drop a spreadsheet of lat/lng data and get an interactive map in seconds. Auto-detects columns, supports up to 5,000 rows, colors points by any category column with a legend, shows every CSV field in a click-popup, and exports clean GeoJSON or KML. Free, no sign-up.

Why this exists — better than free competitors, no account like paid ones

Most free CSV-to-map tools online either gate behind a Google account (Google My Maps), cap at 250 rows on the free tier (BatchGeo, Maptive), or are too basic to be useful (mapcustomizer drops pins but cannot color-categorize and cannot export GeoJSON). Paid tools start at $25/month for individual use.

We built this for the everyday case: you have a spreadsheet with lat/lng, you want to see it on a map, and you want to share or export the result. 5,000 rows is a lot— sufficient for most customer lists, store locators, listing inventories, and field-data visualizations. Color by column is the headline differentiator vs free competitors. Every CSV field appears on click, not just the first three. And it is genuinely free — no watermark, no rate limit, no sign-up.

How to convert a CSV to a map

Five steps. The defaults handle the most common case (lat/lng/name/category) automatically.

1. Paste, upload, or drag-drop your CSV. Paste the CSV text directly into the textarea, click "Upload .csv" to pick a local file, or drag a .csv / .tsv / .txt file onto the textarea area. Up to 5,000 rows. Comma, semicolon, or tab delimiters are auto-detected. The first row should be your header.
2. Confirm the column mapping. The tool auto-detects which columns hold latitude and longitude — first by header name (lat, latitude, lng, lon, longitude…) and then by scanning numeric ranges. If the auto-detection is wrong, override via the dropdowns. The preview table below highlights your picks (green = lat/lng, yellow = label, purple = color).
3. Pick a label column (optional). Choose any column to act as the marker title — the bold heading shown when you click a marker. Common picks: name, title, address, place, city. If you skip this, the popup falls back to the row number.
4. Color by category (optional). Pick a "Color by column" — every unique value in that column gets a distinct color from a 12-color palette, with a legend below the map. Use it for categorical data: country, region, type, status, segment. For a single uniform color, leave it blank and pick from the swatches.
5. Click any point — see all CSV columns. Markers are interactive. Click any one and a popup opens with every column from your CSV (up to 12 fields shown). Pan and zoom; the map auto-frames to fit all your points on first render. Export to GeoJSON or KML when you’re ready.

What people use this tool for

Seven recurring patterns we see in the analytics.

CSV format — which columns the tool looks for

The tool auto-detects column roles by header name (case-insensitive). If your headers do not match these names, override the mapping via the dropdowns. The first row of your CSV should be the header. Quoted fields with embedded commas / newlines / escaped quotes are parsed correctly.

Sample CSV format

name,lat,lng,category,population
Tokyo,35.6762,139.6503,Asia,37400000
New York,40.7128,-74.006,North America,8336000
London,51.5074,-0.1278,Europe,9540000

Two export formats — and which to use

Both exports preserve every column from your original CSV.

How the tool actually works

1. CSV parsing

We use a hand-rolled streaming parser that handles quoted fields with embedded commas, embedded newlines, escaped double-quotes (""), and the UTF-8 Byte Order Mark (BOM) that Excel sometimes prepends. Delimiter is auto-detected by counting ,, ;, and tab characters in the first 4KB of input.

2. Column auto-detection

Two passes. First pass: match header names against a list of common synonyms (lat, latitude, y, lat_dd / lng, lon, longitude, x, lng_dd / etc.). Second pass: for un-detected columns, scan the first 100 rows of each numeric column. Columns whose 85%+ values fall in [-90, 90] are lat candidates; in [-180, 180] are lng candidates. The winner is picked with preference for the column with the more constrained range.

3. Map rendering — WebGL circles

Points render as a MapLibre GL JS circle layer on a GeoJSON source. WebGL renders thousands of circles per frame at 60 FPS — the bottleneck is parsing, not drawing. Circle radius scales with zoom (smaller at world view, larger when zoomed in) so nearby points stay readable at any scale.

4. Click-to-popup

A click handler on the circle layer reads the clicked feature’s properties (which include every original CSV column) and builds a popup with a two-column key/value table. Up to 12 fields are shown; the rest are summarized at the bottom. The popup auto-positions with offset above the clicked point.

5. Color assignment

For categorical color: the tool finds every unique value in your chosen column, assigns each value a color from a 12-color palette in insertion order, and renders each point in its category color via a feature property (__color) read by the circle layer’s paint expression. The legend below the map enumerates the assignment.

6. Exports

GeoJSON wraps the points in a FeatureCollection, with every original CSV column preserved as a feature property. KML wraps each point in a Placemark with the label as name and the full column dump in description. All exports run client-side as Blob downloads — no upload, no server.

SimpleMapLab vs other CSV-to-map tools

Honest comparison. Each tool wins different scenarios — this is a feature checklist, not a value judgement.

Tips for clean CSV-to-map results

• Always include a header row. The first line should be the column names. Without it the tool will treat your first data row as headers and skip it.
• Use decimal degrees, not DMS.Lat 40.7128, not 40°42′46″N. If your data is in DMS format, use our GPS Coordinate Converter to bulk-convert.
• Decimal separator is a period (.), not a comma. Some European exports use comma decimal — switch the locale in your spreadsheet before exporting.
• Watch for swapped lat/lng. If your map looks rotated 90°, the columns may be swapped — use the dropdown to flip them.
• Quote fields with embedded commas. A label like "Smith, John" needs to be wrapped in double-quotes in the CSV.
• Strip leading/trailing whitespace. The parser does it for headers but not for data values, since data may contain meaningful spaces.

Related tools and resources

For converting addresses to lat/lng before mapping (so this tool can plot them): Address to Coordinates. For mapping a list of US ZIP codes specifically: Map with ZIP Codes. For a county-level choropleth from a CSV of FIPS codes + values: Map with Counties. For dropping individual pins by hand (no CSV needed): Pin Drop Map. For converting between coordinate formats: GPS Coordinate Converter. For drawing on top of a map: Map Drawer.

Frequently asked questions

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