AI-generated Key Takeaways
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FeatureCollection.reduceColumnsapplies a reducer to each element of a collection using specified selectors for input. -
The method returns a dictionary of results, with keys corresponding to the output names.
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The usage involves specifying a reducer, input selectors, and optionally weight selectors.
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Arguments include the collection itself, the reducer, a list of selectors for inputs, and an optional list of weight selectors.
Returns a dictionary of results, keyed with the output names.
| Usage | Returns |
|---|---|
FeatureCollection.
reduceColumns
(reducer, selectors, weightSelectors
)
|
Dictionary |
| Argument | Type | Details |
|---|---|---|
|
this:
collection
|
FeatureCollection | The collection to aggregate over. |
reducer
|
Reducer | The reducer to apply. |
selectors
|
List | A selector for each input of the reducer. |
weightSelectors
|
List, default: null | A selector for each weighted input of the reducer. |
Examples
Code Editor (JavaScript)
// FeatureCollection of power plants in Belgium. var fc = ee . FeatureCollection ( 'WRI/GPPD/power_plants' ) . filter ( 'country_lg == "Belgium"' ); // Calculate mean of a single FeatureCollection property. var propMean = fc . reduceColumns ({ reducer : ee . Reducer . mean (), selectors : [ 'gwh_estimt' ] }); print ( 'Mean of a single property' , propMean ); // Calculate mean of multiple FeatureCollection properties. var propsMean = fc . reduceColumns ({ reducer : ee . Reducer . mean (). repeat ( 2 ), selectors : [ 'gwh_estimt' , 'capacitymw' ] }); print ( 'Mean of multiple properties' , propsMean ); // Calculate weighted mean of a single FeatureCollection property. Add a fuel // source weight property to the FeatureCollection. var fuelWeights = ee . Dictionary ({ Wind : 0.9 , Gas : 0.2 , Oil : 0.2 , Coal : 0.1 , Hydro : 0.7 , Biomass : 0.5 , Nuclear : 0.3 }); fc = fc . map ( function ( feature ) { return feature . set ( 'weight' , fuelWeights . getNumber ( feature . get ( 'fuel1' ))); }); var weightedMean = fc . reduceColumns ({ reducer : ee . Reducer . mean (), selectors : [ 'gwh_estimt' ], weightSelectors : [ 'weight' ] }); print ( 'Weighted mean of a single property' , weightedMean );
import ee import geemap.core as geemap
Colab (Python)
# FeatureCollection of power plants in Belgium. fc = ee . FeatureCollection ( 'WRI/GPPD/power_plants' ) . filter ( 'country_lg == "Belgium"' ) # Calculate mean of a single FeatureCollection property. prop_mean = fc . reduceColumns ( ** { 'reducer' : ee . Reducer . mean (), 'selectors' : [ 'gwh_estimt' ] }) display ( 'Mean of a single property:' , prop_mean ) # Calculate mean of multiple FeatureCollection properties. props_mean = fc . reduceColumns ( ** { 'reducer' : ee . Reducer . mean () . repeat ( 2 ), 'selectors' : [ 'gwh_estimt' , 'capacitymw' ] }) display ( 'Mean of multiple properties:' , props_mean ) # Calculate weighted mean of a single FeatureCollection property. Add a fuel # source weight property to the FeatureCollection. def get_fuel ( feature ): return feature . set ( 'weight' , fuel_weights . getNumber ( feature . get ( 'fuel1' ))) fuel_weights = ee . Dictionary ({ 'Wind' : 0.9 , 'Gas' : 0.2 , 'Oil' : 0.2 , 'Coal' : 0.1 , 'Hydro' : 0.7 , 'Biomass' : 0.5 , 'Nuclear' : 0.3 }) fc = fc . map ( get_fuel ) weighted_mean = fc . reduceColumns ( ** { 'reducer' : ee . Reducer . mean (), 'selectors' : [ 'gwh_estimt' ], 'weightSelectors' : [ 'weight' ] }) display ( 'Weighted mean of a single property:' , weighted_mean )
