GeoDataFrame.sjoin

Spatial join of two GeoDataFrames.

Signature

sjoin(
    other,
    how='inner',
    predicate='intersects',
    lsuffix='left',
    rsuffix='right',
    distance=None,
    on_attribute=None,
    **kwargs,
)

Parameters

GeoDataFrame

required

The right GeoDataFrame to join with.

str

default:"'inner'"

The type of join:

‘left’: use keys from left_df; retain only left_df geometry column
‘right’: use keys from right_df; retain only right_df geometry column
‘inner’: use intersection of keys from both dfs; retain only left_df geometry column

str

default:"'intersects'"

Binary predicate. Valid values: ‘intersects’, ‘contains’, ‘within’, ‘dwithin’, ‘touches’, ‘crosses’, ‘overlaps’, ‘covers’, ‘covered_by’

str

default:"'left'"

Suffix to apply to overlapping column names (left GeoDataFrame).

str

default:"'right'"

Suffix to apply to overlapping column names (right GeoDataFrame).

float

default:"None"

Distance for ‘dwithin’ predicate. Required if predicate=‘dwithin’.

(str, list or tuple)

default:"None"

Column name(s) to join on as an additional join restriction. These must be found in both DataFrames.

Additional keyword arguments passed to the spatial join function.

Returns

GeoDataFrame

A GeoDataFrame with the results of the spatial join.

Examples

>>> from shapely.geometry import Point, Polygon
>>> from sedona.spark.geopandas import GeoDataFrame

>>> polygons = GeoDataFrame({
...     'geometry': [Polygon([(0, 0), (0, 1), (1, 1), (1, 0)])],
...     'value': [1]
... })
>>> points = GeoDataFrame({
...     'geometry': [Point(0.5, 0.5), Point(2, 2)],
...     'value': [1, 2]
... })
>>> joined = points.sjoin(polygons)
>>> joined
    geometry_left  value_left            geometry_right  value_right
0  POINT (0.5 0.5)           1  POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))            1

​Signature

​Parameters

​Returns

​Examples

Signature

Parameters

Returns

Examples