ee.FeatureCollection.aggregate_sample_var

  • aggregate_sample_var calculates the sample variance of a specified property within a FeatureCollection.

  • It takes the FeatureCollection and the property name as input.

  • The result is a single number representing the sample variance of the selected property across all features in the collection.

  • This function is useful for understanding the spread or dispersion of a particular feature property within a dataset.

 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