Convert GeoJSON files to CSV, online and free. GISConverter reads your GeoJSON data locally in the browser and writes a CSV file so you can open the attributes in Excel or a spreadsheet, nothing is uploaded, and your data never leaves your computer.
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GeoJSON is the language of web maps. It packs geometry and attributes into one JSON structure, which is great for Leaflet or Mapbox but awkward in a spreadsheet. So people convert GeoJSON to CSV when they want to leave the map and work with the raw table. For example, you might pull features from a web API, then open them in Excel or Google Sheets to sort, filter, or chart the attributes. Analysts also convert to CSV to feed point data into pandas scripts. CSV strips the nesting and gives you flat rows that any tool, GIS or not, can read.
Check how each feature's geometry lands in the CSV. GeoJSON can hold points, lines, and polygons, but a flat CSV row wants simple coordinate columns. Points map cleanly to latitude and longitude. Lines and polygons cannot fit two numbers, so their geometry is usually written as WKT text instead. Also confirm your GeoJSON coordinates are in WGS84, since CSV stores bare numbers with no coordinate system attached.
GeoJSON is where web maps and APIs keep their vector data, with each feature holding a geometry plus a bag of properties. CSV is the flat table you open in a spreadsheet to sort, filter and chart those same records. Converting one to the other pulls features out of the mapping stack and into analysis. In practice you export a FeatureCollection, then read the attributes as plain columns. That means non-mapping colleagues can work the data without touching any GIS tool.
Yes. Each key inside a feature's properties object becomes a CSV column, and every feature becomes one row. The geometry is added as coordinate columns or WKT alongside those attribute columns.
A polygon cannot fit into simple latitude and longitude cells, so its geometry is written as WKT text in a single column. Points, by contrast, become plain lat and lon values that Excel or pandas can read directly.
Point features map cleanly to latitude and longitude columns, one row per feature. Lines and polygons cannot fit two number columns, so their coordinates are written into a single geometry field as WKT. That keeps the shape intact for tools like QGIS or pandas that can parse it back.
CSV is strictly flat, so a nested object or array inside a feature's properties cannot become its own column. Those values are serialized into a single cell as text rather than dropped. For example, a properties block with an address object becomes one string you can split later in Excel.
