ee.FeatureCollection.aggregate_sample_var

  • The aggregate_sample_var method calculates the sample variance of a specified property for objects in a FeatureCollection.

  • This method is available for FeatureCollection objects and returns a single numerical value representing the sample variance.

  • It requires two arguments: the FeatureCollection to operate on and a string specifying the property to analyze.

 Aggregates over a given property of the objects in a collection, calculating the sample variance of the values of the selected property.

UsageReturns
FeatureCollection.aggregate_sample_var(property)Number
ArgumentTypeDetails
this: collectionFeatureCollectionThe collection to aggregate over.
propertyStringThe property to use from each element of the collection.

Examples

Code Editor (JavaScript)

// FeatureCollection of power plants in Belgium.
var fc = ee.FeatureCollection('WRI/GPPD/power_plants')
             .filter('country_lg == "Belgium"');

print('Sample variance of power plant capacities (MW)',
      fc.aggregate_sample_var('capacitymw'));  // 217604.420018647

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

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"')

print('Sample variance of power plant capacities (MW):',
      fc.aggregate_sample_var('capacitymw').getInfo())  # 217604.420018647