![]() ![]() The values for predicate correspond to the names of geometric binary predicates and depend on the spatial Object to another, based on their geometric relationship. The predicate argument specifies how geopandas decides whether or not to join the attributes of one GeoDataFrame.sjoin() has two core arguments: how and predicate. ![]() Binary Predicate Joins #īinary predicate joins are available via GeoDataFrame.sjoin(). It is recommended to use methods as the functions may be deprecated in the future. GeoDataFrame.sjoin_nearest(): joins based on proximity, with the ability to set a maximum search radius.įor historical reasons, both methods are also available as top-level functions sjoin() and sjoin_nearest(). GeoDataFrame.sjoin(): joins based on binary predicates (intersects, contains, etc.) GeoPandas provides two spatial-join functions: ![]() sjoin ( countries, how = "inner", predicate = 'intersects' ) In : cities_with_country. # Want to merge so we can get each city's country. # One GeoDataFrame of countries, one of Cities. In a Spatial Join, two geometry objects are merged based on their spatial relationship to one another. merge ( country_names, on = 'iso_a3' ) In : country_shapes. Sahara ESH 3 Canada CAN 4 United States of America USA # Merge with `merge` method on shared variable (iso codes): In : country_shapes = country_shapes. head () Out: name iso_a3 0 Fiji FJI 1 Tanzania TZA 2 W. USA # `country_names` is DataFrame with country names and iso codes In : country_names. # `country_shapes` is GeoDataFrame with country shapes and iso codes In : country_shapes.
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