ee.FeatureCollection.aggregate_total_sd

  • aggregate_total_sd calculates the total standard deviation of a specified property across all features within a FeatureCollection.

  • It takes a FeatureCollection and the property name as input, returning the total standard deviation as a number.

  • This function is useful for understanding the dispersion or variability of a specific property within a dataset, like the capacities of power plants in a region.

 Aggregates over a given property of the objects in a collection, calculating the total std. deviation of the values of the selected property.

UsageReturns
FeatureCollection.aggregate_total_sd(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('Total std. deviation of power plant capacities (MW)',
      fc.aggregate_total_sd('capacitymw'));  // 462.9334545609107

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('Total std. deviation of power plant capacities (MW):',
      fc.aggregate_total_sd('capacitymw').getInfo())  # 462.9334545609107