ee.FeatureCollection.aggregate_total_sd
Aggregates over a given property of the objects in a collection, calculating the total std. deviation of the values of the selected property.
Usage | Returns |
---|
FeatureCollection.aggregate_total_sd(property) | Number |
Argument | Type | Details |
---|
this: collection | FeatureCollection | The collection to aggregate over. |
property | String | The property to use from each element of the collection. |
Examples
// 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
# 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
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["`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."]]],["The `aggregate_total_sd` function calculates the total standard deviation of a specified property across a FeatureCollection. It takes the collection and the property name as input, returning a numerical value representing the total standard deviation. In practice, you can use the function to calculate the total standard deviation of power plant capacities (MW) in a given Feature Collection, as shown in the provided examples. Both Python and JavaScript code snippets are available.\n"]]