<jupyter_start><jupyter_text>[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/giswqs/gee-tutorials/blob/master/ImageCollection/cloud_free_composite.ipynb)<jupyter_code>import ee
import geemap
Map = geemap.Map()
Map
states = ee.FeatureCollection('TIGER/2018/States')
TN = states.filter(ee.Filter.eq("NAME", "Tennessee"))
Map.addLayer(TN, {}, "Tennessee")
years = ee.List.sequence(2013, 2020)
years.getInfo()
def yearly_image(year):
    
    start_date = ee.Date.fromYMD(year, 1, 1) 
    end_date = start_date.advance(1, "year")
    
    collection = ee.ImageCollection('LANDSAT/LC08/C01/T1') \
        .filterDate(start_date, end_date) \
        .filterBounds(TN) 
    
    image =  ee.Algorithms.Landsat.simpleComposite(collection).clipToCollection(TN)

    return image
images = years.map(yearly_image)
vis_params = {'bands': ['B5',  'B4',  'B3'], 'max': 128}
for index in range(0, 8):
    image = ee.Image(images.get(index))
    layer_name = "Image " + str(index + 2013)
    Map.addLayer(image, vis_params, layer_name)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1585144927536232, 'fraction_numerical': 0.028985507246376812, 'mean_word_length': 4.58080808080808, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '30171', 'license': 'MIT', 'n_tokens_mistral': 454, 'n_tokens_neox': 413, 'n_words': 61, 'path': 'ImageCollection/cloud_free_composite.ipynb', 'repo_name': 'giswqs/gee-tutorials', 'size': '1104'}