ee.FeatureCollection.aggregate_histogram
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 a histogram of the selected property.
| שימוש | החזרות |
|---|
FeatureCollection.aggregate_histogram(property) | מילון |
| 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('Histogram of power plant capacities (MW)',
fc.aggregate_histogram('capacitymw')); // Dictionary
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)
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
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\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```"]]
