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ee.FeatureCollection.aggregate_histogram
Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
Aggrega una determinata proprietà degli oggetti in una raccolta, calcolando un istogramma della proprietà selezionata.
Utilizzo | Resi |
---|
FeatureCollection.aggregate_histogram(property) | Dizionario |
Argomento | Tipo | Dettagli |
---|
questo: collection | FeatureCollection | La raccolta su cui eseguire l'aggregazione. |
property | Stringa | La proprietà da utilizzare per ogni elemento della raccolta. |
Esempi
Editor di codice (JavaScript)
// FeatureCollection of power plants in Belgium.
var fc = ee.FeatureCollection('WRI/GPPD/power_plants')
.filter('country_lg == "Belgium"');
print('Histogram of power plant capacities (MW)',
fc.aggregate_histogram('capacitymw')); // Dictionary
Configurazione di Python
Consulta la pagina
Ambiente Python per informazioni sull'API Python e sull'utilizzo di
geemap
per lo sviluppo interattivo.
import ee
import geemap.core as geemap
Colab (Python)
from pprint import pprint
# FeatureCollection of power plants in Belgium.
fc = ee.FeatureCollection('WRI/GPPD/power_plants').filter(
'country_lg == "Belgium"')
print('Histogram of power plant capacities (MW):')
pprint(fc.aggregate_histogram('capacitymw').getInfo()) # Dictionary
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-26 UTC.
[null,null,["Ultimo aggiornamento 2025-07-26 UTC."],[[["\u003cp\u003eComputes a histogram for a specified property within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eReturns a dictionary where keys represent property value ranges and values represent the frequency of features within that range.\u003c/p\u003e\n"],["\u003cp\u003eUseful for understanding the distribution of a specific attribute, such as the capacity of power plants in a region.\u003c/p\u003e\n"]]],["The `aggregate_histogram` method calculates a histogram for a specified property across a FeatureCollection. It takes the collection and the property name as input. The output is a dictionary representing the histogram. In the provided examples, a FeatureCollection of Belgian power plants is used, and a histogram of their capacities (in MW) is generated using `aggregate_histogram('capacitymw')`. The method works on both the Javascript and Python Earth Engine APIs.\n"],null,["# ee.FeatureCollection.aggregate_histogram\n\nAggregates over a given property of the objects in a collection, calculating a histogram of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|---------------------------------------------------|------------|\n| FeatureCollection.aggregate_histogram`(property)` | Dictionary |\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('Histogram of power plant capacities (MW)',\n fc.aggregate_histogram('capacitymw')); // Dictionary\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\nfrom pprint import pprint\n\n# FeatureCollection of power plants in Belgium.\nfc = ee.FeatureCollection('WRI/GPPD/power_plants').filter(\n 'country_lg == \"Belgium\"')\n\nprint('Histogram of power plant capacities (MW):')\npprint(fc.aggregate_histogram('capacitymw').getInfo()) # Dictionary\n```"]]