ee.FeatureCollection.aggregate_mean
קל לארגן דפים בעזרת אוספים
אפשר לשמור ולסווג תוכן על סמך ההעדפות שלך.
Aggregates over a given property of the objects in a collection, calculating the mean of the selected property.
| שימוש | החזרות |
|---|
FeatureCollection.aggregate_mean(property) | מספר |
| ארגומנט | סוג | פרטים |
|---|
זה: collection | FeatureCollection | האוסף לצבירה. |
property | מחרוזת | המאפיין שבו רוצים להשתמש מכל רכיב באוסף. |
דוגמאות
עורך הקוד (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
הגדרת Python
מידע על Python API ועל שימוש ב-geemap לפיתוח אינטראקטיבי מופיע בדף
Python Environment.
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
אלא אם צוין אחרת, התוכן של דף זה הוא ברישיון Creative Commons Attribution 4.0 ודוגמאות הקוד הן ברישיון Apache 2.0. לפרטים, ניתן לעיין במדיניות האתר Google Developers. Java הוא סימן מסחרי רשום של חברת Oracle ו/או של השותפים העצמאיים שלה.
עדכון אחרון: 2025-07-26 (שעון UTC).
[null,null,["עדכון אחרון: 2025-07-26 (שעון 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```"]]
