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ee.FeatureCollection.aggregate_total_var
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Aggregates over a given property of the objects in a collection, calculating the total variance of the values of the selected property.
| Usage | Returns | FeatureCollection.aggregate_total_var(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 variance of power plant capacities (MW)',
fc.aggregate_total_var('capacitymw')); // 214307.38335169878
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 variance of power plant capacities (MW):',
fc.aggregate_total_var('capacitymw').getInfo()) # 214307.38335169878
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_var\u003c/code\u003e calculates the total variance of a specified property across all features within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eIt takes the FeatureCollection and the property name as input and returns a numerical value representing the total variance.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for understanding the dispersion or spread of a property's values within a dataset.\u003c/p\u003e\n"],["\u003cp\u003eThe example demonstrates calculating the total variance of power plant capacities in Belgium using a publicly available dataset.\u003c/p\u003e\n"]]],["The `aggregate_total_var` function calculates the total variance of a specified property across a FeatureCollection. It takes a FeatureCollection and a property name as input. The function then computes the total variance of the property's values for all objects within the collection. The output is a numerical value representing this total variance. For instance, the example demonstrates calculating the total variance of power plant capacities in Belgium using this method.\n"],null,["# ee.FeatureCollection.aggregate_total_var\n\nAggregates over a given property of the objects in a collection, calculating the total variance of the values of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|---------------------------------------------------|---------|\n| FeatureCollection.aggregate_total_var`(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 variance of power plant capacities (MW)',\n fc.aggregate_total_var('capacitymw')); // 214307.38335169878\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 variance of power plant capacities (MW):',\n fc.aggregate_total_var('capacitymw').getInfo()) # 214307.38335169878\n```"]]