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As with Images, there are a variety of ways to get information about anImageCollection. The collection can be printed directly to the console,
but the console printout is limited to 5000 elements. Collections larger than 5000
images will need to be filtered before printing. Printing a large collection will be
correspondingly slower. The following example shows various ways of getting information
about image collections programmatically:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-03-11 UTC."],[[["\u003cp\u003eThis guide demonstrates how to programmatically retrieve information from Earth Engine ImageCollections, such as size, date range, image properties, and specific images.\u003c/p\u003e\n"],["\u003cp\u003eYou can print an ImageCollection to the console, but for collections larger than 5000 images, filtering is necessary before printing to avoid slowdowns.\u003c/p\u003e\n"],["\u003cp\u003eExamples are provided using the JavaScript and Python APIs for tasks like filtering, sorting, getting statistics, and limiting the collection size.\u003c/p\u003e\n"],["\u003cp\u003eIt shows how to get specific images from the collection, including the least cloudy or the most recent ones, based on properties and sorting.\u003c/p\u003e\n"],["\u003cp\u003eThe code snippets are readily usable in Code Editor, Colab, or any Python environment set up for Earth Engine, with \u003ccode\u003egeemap\u003c/code\u003e suggested for interactive Python development.\u003c/p\u003e\n"]]],[],null,["# ImageCollection Information and Metadata\n\nAs with Images, there are a variety of ways to get information about an\n`ImageCollection`. The collection can be printed directly to the console,\nbut the console printout is limited to 5000 elements. Collections larger than 5000\nimages will need to be filtered before printing. Printing a large collection will be\ncorrespondingly slower. The following example shows various ways of getting information\nabout image collections programmatically:\n\n### Code Editor (JavaScript)\n\n```javascript\n// Load a Landsat 8 ImageCollection for a single path-row.\nvar collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')\n .filter(ee.Filter.eq('WRS_PATH', 44))\n .filter(ee.Filter.eq('WRS_ROW', 34))\n .filterDate('2014-03-01', '2014-08-01');\nprint('Collection: ', collection);\n\n// Get the number of images.\nvar count = collection.size();\nprint('Count: ', count);\n\n// Get the date range of images in the collection.\nvar range = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])\nprint('Date range: ', ee.Date(range.get('min')), ee.Date(range.get('max')))\n\n// Get statistics for a property of the images in the collection.\nvar sunStats = collection.aggregate_stats('SUN_ELEVATION');\nprint('Sun elevation statistics: ', sunStats);\n\n// Sort by a cloud cover property, get the least cloudy image.\nvar image = ee.Image(collection.sort('CLOUD_COVER').first());\nprint('Least cloudy image: ', image);\n\n// Limit the collection to the 10 most recent images.\nvar recent = collection.sort('system:time_start', false).limit(10);\nprint('Recent images: ', recent);\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# Load a Landsat 8 ImageCollection for a single path-row.\ncollection = (\n ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')\n .filter(ee.Filter.eq('WRS_PATH', 44))\n .filter(ee.Filter.eq('WRS_ROW', 34))\n .filterDate('2014-03-01', '2014-08-01')\n)\ndisplay('Collection:', collection)\n\n# Get the number of images.\ncount = collection.size()\ndisplay('Count:', count)\n\n# Get the date range of images in the collection.\nrange = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])\ndisplay('Date range:', ee.Date(range.get('min')), ee.Date(range.get('max')))\n\n# Get statistics for a property of the images in the collection.\nsun_stats = collection.aggregate_stats('SUN_ELEVATION')\ndisplay('Sun elevation statistics:', sun_stats)\n\n# Sort by a cloud cover property, get the least cloudy image.\nimage = ee.Image(collection.sort('CLOUD_COVER').first())\ndisplay('Least cloudy image:', image)\n\n# Limit the collection to the 10 most recent images.\nrecent = collection.sort('system:time_start', False).limit(10)\ndisplay('Recent images:', recent)\n```"]]
