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ee.FeatureCollection.aggregate_sample_sd
Mantenha tudo organizado com as coleções
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Agrega uma determinada propriedade dos objetos em uma coleção, calculando o desvio padrão da amostra dos valores da propriedade selecionada.
| Uso | Retorna |
|---|
FeatureCollection.aggregate_sample_sd(property) | Número |
| Argumento | Tipo | Detalhes |
|---|
isso: collection | FeatureCollection | A coleção para agregar. |
property | String | A propriedade a ser usada de cada elemento da coleção. |
Exemplos
Editor de código (JavaScript)
// FeatureCollection of power plants in Belgium.
var fc = ee.FeatureCollection('WRI/GPPD/power_plants')
.filter('country_lg == "Belgium"');
print('Sample std. deviation of power plant capacities (MW)',
fc.aggregate_sample_sd('capacitymw')); // 466.480889231
Configuração do Python
Consulte a página
Ambiente Python para informações sobre a API Python e como usar
geemap para desenvolvimento interativo.
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 std. deviation of power plant capacities (MW):',
fc.aggregate_sample_sd('capacitymw').getInfo()) # 466.480889231
Exceto em caso de indicação contrária, o conteúdo desta página é licenciado de acordo com a Licença de atribuição 4.0 do Creative Commons, e as amostras de código são licenciadas de acordo com a Licença Apache 2.0. Para mais detalhes, consulte as políticas do site do Google Developers. Java é uma marca registrada da Oracle e/ou afiliadas.
Última atualização 2025-07-26 UTC.
[null,null,["Última atualização 2025-07-26 UTC."],[[["\u003cp\u003e\u003ccode\u003eaggregate_sample_sd\u003c/code\u003e calculates the sample standard deviation of a specified property within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eIt takes the FeatureCollection and the property name as input.\u003c/p\u003e\n"],["\u003cp\u003eThe function returns a single numeric value representing the sample standard deviation.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for understanding the dispersion or variability of a property within a collection of geographic features.\u003c/p\u003e\n"]]],["The `aggregate_sample_sd` function calculates the sample 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 standard deviation. For instance, applied to a FeatureCollection of power plants, it can compute the sample standard deviation of their capacities. The example shows calculating the sample standard deviation of power plant `capacitymw` for power plants in Belgium.\n"],null,["# ee.FeatureCollection.aggregate_sample_sd\n\nAggregates over a given property of the objects in a collection, calculating the sample std. deviation of the values of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|---------------------------------------------------|---------|\n| FeatureCollection.aggregate_sample_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('Sample std. deviation of power plant capacities (MW)',\n fc.aggregate_sample_sd('capacitymw')); // 466.480889231\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('Sample std. deviation of power plant capacities (MW):',\n fc.aggregate_sample_sd('capacitymw').getInfo()) # 466.480889231\n```"]]
