Duyuru:
15 Nisan 2025'ten önce Earth Engine'i kullanmak için kaydedilen tüm ticari olmayan projelerin Earth Engine erişimini sürdürmek için
ticari olmayan uygunluğu doğrulaması gerekir.
ee.FeatureCollection.aggregate_stats
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
Bir koleksiyondaki nesnelerin belirli bir özelliğini toplar ve seçilen özelliğin toplamını, minimum değerini, maksimum değerini, ortalamasını, örnek standart sapmasını, örnek varyansını, toplam standart sapmasını ve toplam varyansını hesaplar.
| Kullanım | İadeler |
|---|
FeatureCollection.aggregate_stats(property) | Sözlük |
| Bağımsız Değişken | Tür | Ayrıntılar |
|---|
bu: collection | FeatureCollection | Üzerinde toplama işlemi yapılacak koleksiyon. |
property | Dize | Koleksiyonun her öğesinden kullanılacak özellik. |
Örnekler
Kod Düzenleyici (JavaScript)
// FeatureCollection of power plants in Belgium.
var fc = ee.FeatureCollection('WRI/GPPD/power_plants')
.filter('country_lg == "Belgium"');
print('Power plant capacities (MW) summary stats',
fc.aggregate_stats('capacitymw'));
/**
* Expected ee.Dictionary output
*
* {
* "max": 2910,
* "mean": 201.34242424242427,
* "min": 1.8,
* "sample_sd": 466.4808892319684,
* "sample_var": 217604.42001864797,
* "sum": 13288.600000000002,
* "sum_sq": 16819846.24,
* "total_count": 66,
* "total_sd": 462.9334545609107,
* "total_var": 214307.38335169878,
* "valid_count": 66,
* "weight_sum": 66,
* "weighted_sum": 13288.600000000002
* }
*/
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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('Power plant capacities (MW) summary stats:')
pprint(fc.aggregate_stats('capacitymw').getInfo())
# Expected ee.Dictionary output
# {
# "max": 2910,
# "mean": 201.34242424242427,
# "min": 1.8,
# "sample_sd": 466.4808892319684,
# "sample_var": 217604.42001864797,
# "sum": 13288.600000000002,
# "sum_sq": 16819846.24,
# "total_count": 66,
# "total_sd": 462.9334545609107,
# "total_var": 214307.38335169878,
# "valid_count": 66,
# "weight_sum": 66,
# "weighted_sum": 13288.600000000002
# }
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[[["\u003cp\u003eCalculates descriptive statistics (sum, min, max, mean, standard deviation, and variance) for a specified property within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eAccepts a FeatureCollection and the property name as input.\u003c/p\u003e\n"],["\u003cp\u003eReturns a dictionary containing the calculated statistics.\u003c/p\u003e\n"],["\u003cp\u003eUseful for understanding the distribution and central tendency of a property across features.\u003c/p\u003e\n"],["\u003cp\u003eExamples demonstrate using the function with power plant data to calculate capacity statistics.\u003c/p\u003e\n"]]],[],null,["# ee.FeatureCollection.aggregate_stats\n\nAggregates over a given property of the objects in a collection, calculating the sum, min, max, mean, sample standard deviation, sample variance, total standard deviation and total variance of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-----------------------------------------------|------------|\n| FeatureCollection.aggregate_stats`(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('Power plant capacities (MW) summary stats',\n fc.aggregate_stats('capacitymw'));\n\n/**\n * Expected ee.Dictionary output\n *\n * {\n * \"max\": 2910,\n * \"mean\": 201.34242424242427,\n * \"min\": 1.8,\n * \"sample_sd\": 466.4808892319684,\n * \"sample_var\": 217604.42001864797,\n * \"sum\": 13288.600000000002,\n * \"sum_sq\": 16819846.24,\n * \"total_count\": 66,\n * \"total_sd\": 462.9334545609107,\n * \"total_var\": 214307.38335169878,\n * \"valid_count\": 66,\n * \"weight_sum\": 66,\n * \"weighted_sum\": 13288.600000000002\n * }\n */\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('Power plant capacities (MW) summary stats:')\npprint(fc.aggregate_stats('capacitymw').getInfo())\n\n# Expected ee.Dictionary output\n\n# {\n# \"max\": 2910,\n# \"mean\": 201.34242424242427,\n# \"min\": 1.8,\n# \"sample_sd\": 466.4808892319684,\n# \"sample_var\": 217604.42001864797,\n# \"sum\": 13288.600000000002,\n# \"sum_sq\": 16819846.24,\n# \"total_count\": 66,\n# \"total_sd\": 462.9334545609107,\n# \"total_var\": 214307.38335169878,\n# \"valid_count\": 66,\n# \"weight_sum\": 66,\n# \"weighted_sum\": 13288.600000000002\n# }\n```"]]
