Which column names are auto-detected?

Common names like lat, latitude, y, lon, lng, long, longitude and x are matched case-insensitively. If your headers differ, just pick the correct columns from the dropdowns.

What geometry does it produce?

Each CSV row becomes a GeoJSON Point feature whose coordinates are written in [longitude, latitude] order, exactly as RFC 7946 requires.

What happens to my other columns?

Every non-coordinate column is copied into the feature's properties object. Numeric-looking values are converted to numbers so they stay usable for styling and filtering.

Is my data uploaded anywhere?

No. Parsing and conversion run entirely in your browser with JavaScript, so coordinates and properties never leave your machine.

What if a row has a blank or invalid coordinate?

Rows whose chosen latitude or longitude cannot be parsed as a finite number are skipped, and the tool reports how many rows were dropped so you can fix the source.

CSV to GeoJSON Converter

Convert CSV to GeoJSON in your browser

This tool turns a plain CSV with latitude and longitude columns into a valid GeoJSON FeatureCollection of point features, ready to drop into Leaflet, Mapbox, QGIS, or any GIS tool that reads GeoJSON. It is built for analysts and developers who have tabular location data and need map-ready output without writing a script.

How it works

The converter first parses the CSV, respecting quoted fields that contain commas or line breaks (RFC 4180 quoting). It reads the header row, then scans those headers to auto-detect the latitude and longitude columns by matching common names such as lat, latitude, lon, lng and longitude. For every data row it builds a Point geometry with coordinates written in [longitude, latitude] order — the order the GeoJSON spec mandates — and copies all remaining columns into the feature’s properties. Values that look numeric are converted to numbers so they work with data-driven styling.

Example

This CSV:

name,lat,lon,population
London,51.5074,-0.1278,8900000
Hanoi,21.0278,105.8342,8050000

becomes a FeatureCollection where each city is a Point feature with name and population in its properties. All of this happens locally — nothing is uploaded.