How to get a list of the mean of the pixels of each image from a ee.ImageCollection?

[ErikSeras]

Hi,

I would like to know how I can get a list of the mean of the pixels of each image from a ee.ImageCollection. In this case, from s5_no2_day.

import ee
import geemap
import pandas as pd
from datetime import datetime

try:
    ee.Initialize()
except Exception as e:
    ee.Authenticate()
    ee.Initialize()

# create a collection with 1 image for each day
def image_per_day(d):
    start = ee.Date(d)
    end = start.advance(1, 'day')
    image = s5_no2.filterDate(start, end) \
        .filterBounds(lima_metropolitana) \
        .reduce(ee.Reducer.mean()).clip(lima_metropolitana).multiply(1000000)

    return image

# get dates in an interval
def get_dates(inicio, fin):
    dates = (
        pd.date_range(inicio, fin , freq='1d')
    ).strftime("%Y-%m-%d").tolist()
    return dates

# dataset
s5_no2 = ee.ImageCollection("COPERNICUS/S5P/NRTI/L3_NO2") \
    .select("NO2_column_number_density")

# roi
lima_metropolitana = ee.FeatureCollection("FAO/GAUL/2015/level2") \
    .filterMetadata("ADM1_NAME", "equals", "Lima") \
    .filterMetadata("ADM2_NAME", "equals", "Lima")

# dates
october = ee.List(get_dates("2019-10-01", "2019-10-31"))

# image per day
s5_no2_day = ee.ImageCollection(october.map(image_per_day))

[giswqs]

You can use zonal statistics. Simply convert a collection to image using .toBands() and then use it with the zonal_statistics() function.

https://geemap.org/notebooks/12_zonal_statistics
https://geemap.org/common/#geemap.common.zonal_statistics

[ErikSeras]

Thank you very much @giswqs.

[ErikSeras]

With this supplemental code I was able to answer my question.

def get_mean_per_image(a):
    start = ee.Date(a)
    end = start.advance(1, 'day')
    image = s5_no2.filterDate(start, end) \
        .filterBounds(lima_metropolitana) \
        .reduce(ee.Reducer.mean()).clip(lima_metropolitana).multiply(1000000)

    mean_image = image.reduceRegion(
        reducer = ee.Reducer.mean(),
        geometry = lima_metropolitana,
        scale = 1200,
        maxPixels = 10000000
    )
    return mean_image

days = ee.List(get_dates("2019-10-01", "2019-10-31"))

s5_no2_mean_values= days.map(get_mean_per_image)

mean_values = s5_no2_mean_values.getInfo()

# get list of mean values
mean_values_list = [d['NO2_column_number_density_mean'] for d in mean_values]