ee.FeatureCollection.aggregate_total_var
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 total variance of the values of the selected property.
| שימוש | החזרות |
|---|
FeatureCollection.aggregate_total_var(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('Total variance of power plant capacities (MW)',
fc.aggregate_total_var('capacitymw')); // 214307.38335169878
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('Total variance of power plant capacities (MW):',
fc.aggregate_total_var('capacitymw').getInfo()) # 214307.38335169878
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\u003e\u003ccode\u003eaggregate_total_var\u003c/code\u003e calculates the total variance of a specified property across all features within a FeatureCollection.\u003c/p\u003e\n"],["\u003cp\u003eIt takes the FeatureCollection and the property name as input and returns a numerical value representing the total variance.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for understanding the dispersion or spread of a property's values within a dataset.\u003c/p\u003e\n"],["\u003cp\u003eThe example demonstrates calculating the total variance of power plant capacities in Belgium using a publicly available dataset.\u003c/p\u003e\n"]]],["The `aggregate_total_var` function calculates the total variance of a specified property across a FeatureCollection. It takes a FeatureCollection and a property name as input. The function then computes the total variance of the property's values for all objects within the collection. The output is a numerical value representing this total variance. For instance, the example demonstrates calculating the total variance of power plant capacities in Belgium using this method.\n"],null,["# ee.FeatureCollection.aggregate_total_var\n\nAggregates over a given property of the objects in a collection, calculating the total variance of the values of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|---------------------------------------------------|---------|\n| FeatureCollection.aggregate_total_var`(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('Total variance of power plant capacities (MW)',\n fc.aggregate_total_var('capacitymw')); // 214307.38335169878\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('Total variance of power plant capacities (MW):',\n fc.aggregate_total_var('capacitymw').getInfo()) # 214307.38335169878\n```"]]
