geopandas.GeoDataFrame.to_json#

GeoDataFrame.to_json(na='null', show_bbox=False, drop_id=False, **kwargs)[source]#

Returns a GeoJSON representation of the GeoDataFrame as a string.

Parameters
na{‘null’, ‘drop’, ‘keep’}, default ‘null’

Indicates how to output missing (NaN) values in the GeoDataFrame. See below.

show_bboxbool, optional, default: False

Include bbox (bounds) in the geojson

drop_idbool, default: False

Whether to retain the index of the GeoDataFrame as the id property in the generated GeoJSON. Default is False, but may want True if the index is just arbitrary row numbers.

See also

GeoDataFrame.to_file

write GeoDataFrame to file

Notes

The remaining kwargs are passed to json.dumps().

Missing (NaN) values in the GeoDataFrame can be represented as follows:

  • null: output the missing entries as JSON null.

  • drop: remove the property from the feature. This applies to each feature individually so that features may have different properties.

  • keep: output the missing entries as NaN.

Examples

>>> from shapely.geometry import Point
>>> d = {'col1': ['name1', 'name2'], 'geometry': [Point(1, 2), Point(2, 1)]}
>>> gdf = geopandas.GeoDataFrame(d, crs="EPSG:4326")
>>> gdf
    col1                 geometry
0  name1  POINT (1.00000 2.00000)
1  name2  POINT (2.00000 1.00000)

>>> gdf.to_json()
'{"type": "FeatureCollection", "features": [{"id": "0", "type": "Feature", "properties": {"col1": "name1"}, "geometry": {"type": "Point", "coordinates": [1.0, 2.0]}}, {"id": "1", "type": "Feature", "properties": {"col1": "name2"}, "geometry": {"type": "Point", "coordinates": [2.0, 1.0]}}]}'

Alternatively, you can write GeoJSON to file:

>>> gdf.to_file(path, driver="GeoJSON")