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ee.FeatureCollection.aggregate_total_sd
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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
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
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["\u003cp\u003e\u003ccode\u003eaggregate_total_sd\u003c/code\u003e calculates the total standard deviation of a specified property across all features within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eIt takes a FeatureCollection and the property name as input, returning the total standard deviation as a number.\u003c/p\u003e\n"],["\u003cp\u003eThis 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.\u003c/p\u003e\n"]]],["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"],null,["# ee.FeatureCollection.aggregate_total_sd\n\nAggregates over a given property of the objects in a collection, calculating the total std. deviation of the values of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|--------------------------------------------------|---------|\n| FeatureCollection.aggregate_total_sd`(property)` | Number |\n\n| Argument | Type | Details |\n|--------------------|-------------------|----------------------------------------------------------|\n| this: `collection` | FeatureCollection | The collection to aggregate over. |\n| `property` | String | The property to use from each element of the collection. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// FeatureCollection of power plants in Belgium.\nvar fc = ee.FeatureCollection('WRI/GPPD/power_plants')\n .filter('country_lg == \"Belgium\"');\n\nprint('Total std. deviation of power plant capacities (MW)',\n fc.aggregate_total_sd('capacitymw')); // 462.9334545609107\n```\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\n# FeatureCollection of power plants in Belgium.\nfc = ee.FeatureCollection('WRI/GPPD/power_plants').filter(\n 'country_lg == \"Belgium\"')\n\nprint('Total std. deviation of power plant capacities (MW):',\n fc.aggregate_total_sd('capacitymw').getInfo()) # 462.9334545609107\n```"]]