Pengumuman: Semua project nonkomersial yang terdaftar untuk menggunakan Earth Engine sebelum
15 April 2025 harus
memverifikasi kelayakan nonkomersial untuk mempertahankan akses Earth Engine.
ee.FeatureCollection.aggregate_mean
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Menggabungkan properti tertentu dari objek dalam koleksi, menghitung rata-rata properti yang dipilih.
| Penggunaan | Hasil |
|---|
FeatureCollection.aggregate_mean(property) | Angka |
| Argumen | Jenis | Detail |
|---|
ini: collection | FeatureCollection | Koleksi yang akan digabungkan. |
property | String | Properti yang akan digunakan dari setiap elemen koleksi. |
Contoh
Code Editor (JavaScript)
// FeatureCollection of power plants in Belgium.
var fc = ee.FeatureCollection('WRI/GPPD/power_plants')
.filter('country_lg == "Belgium"');
print('Mean of power plant capacities (MW)',
fc.aggregate_mean('capacitymw')); // 201.342424242
Penyiapan Python
Lihat halaman
Lingkungan Python untuk mengetahui informasi tentang Python API dan penggunaan
geemap untuk pengembangan interaktif.
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('Mean of power plant capacities (MW):',
fc.aggregate_mean('capacitymw').getInfo()) # 201.342424242
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[[["\u003cp\u003eCalculates the mean (average) value of a specified property across all features within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eAccepts a FeatureCollection and the name of the property to analyze as input.\u003c/p\u003e\n"],["\u003cp\u003eReturns a single numerical value representing the calculated mean.\u003c/p\u003e\n"],["\u003cp\u003eUseful for understanding the central tendency of a property within a dataset, such as average power plant capacity in a region.\u003c/p\u003e\n"]]],["The `aggregate_mean` function calculates the mean of a specified property across a FeatureCollection. It takes the `FeatureCollection` and the `property` name as inputs. The function returns a Number representing the mean value. For example, using a FeatureCollection of power plants, `aggregate_mean('capacitymw')` computes the mean power plant capacity in megawatts. The provided examples showcase how to implement it in both JavaScript and Python environments.\n"],null,["# ee.FeatureCollection.aggregate_mean\n\nAggregates over a given property of the objects in a collection, calculating the mean of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|----------------------------------------------|---------|\n| FeatureCollection.aggregate_mean`(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('Mean of power plant capacities (MW)',\n fc.aggregate_mean('capacitymw')); // 201.342424242\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('Mean of power plant capacities (MW):',\n fc.aggregate_mean('capacitymw').getInfo()) # 201.342424242\n```"]]
