How to deal with ImageCollection.toBands: Too many bands (more than 5000)

[ambarja]

Hi, I am recently using geemap on google colab and this is fantastic!
However I have a problem when I want to extract large time series from chirps , here the error 👇.

import ee
import geemap
import geopandas as gpd
import pandas as pd
import os

dist = ee.FeatureCollection('users/geografo2023/distritos_inei_2017')
start_date = '2000-01-01'
end_date = '2023-12-31'

chirps = ee.ImageCollection("UCSB-CHG/CHIRPS/DAILY")\
          .select('precipitation')\
          .filterDate(start_date,end_date)\
          .toBands()

out_dir = os.path.join(os.path.expanduser("~"), "/content/descargas")
out_chrips_stats = os.path.join(out_dir, "chirps_stats.csv")
geemap.zonal_stats(chirps, dist, out_chrips_stats, stat_type="MEAN", scale=5566)

Computing statistics ...
---------------------------------------------------------------------------
HttpError                                 Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/ee/data.py](https://localhost:8080/#) in _execute_cloud_call(call, num_retries)
    401   try:
--> 402     return call.execute(num_retries=num_retries)
    403   except googleapiclient.errors.HttpError as e:

8 frames
HttpError: <HttpError 400 when requesting https://earthengine.googleapis.com/v1/projects/ee-geografope/value:compute?prettyPrint=false&alt=json returned "ImageCollection.toBands: Too many bands (more than 5000).". Details: "ImageCollection.toBands: Too many bands (more than 5000).">

During handling of the above exception, another exception occurred:

EEException                               Traceback (most recent call last)
EEException: ImageCollection.toBands: Too many bands (more than 5000).

During handling of the above exception, another exception occurred:

Exception                                 Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/geemap/common.py](https://localhost:8080/#) in zonal_stats(in_value_raster, in_zone_vector, out_file_path, stat_type, scale, crs, tile_scale, return_fc, verbose, timeout, proxies, **kwargs)
   7039             ee_export_vector(result, filename, timeout=timeout, proxies=proxies)
   7040     except Exception as e:
-> 7041         raise Exception(e)
   7042 
   7043 

Exception: ImageCollection.toBands: Too many bands (more than 5000).

[ambarja]

I reduce the range but I have a similar error

start_date = '2000-01-01'
end_date = '2010-12-31'
chirps = ee.ImageCollection("UCSB-CHG/CHIRPS/DAILY")\
          .select('precipitation')\
          .filterDate(start_date,end_date)\
          .toBands()

Computing statistics ...
---------------------------------------------------------------------------
HttpError                                 Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/ee/data.py](https://localhost:8080/#) in _execute_cloud_call(call, num_retries)
    401   try:
--> 402     return call.execute(num_retries=num_retries)
    403   except googleapiclient.errors.HttpError as e:

8 frames
HttpError: <HttpError 400 when requesting https://earthengine.googleapis.com/v1/projects/ee-geografope/value:compute?prettyPrint=false&alt=json returned "Computed value is too large.". Details: "Computed value is too large.">

During handling of the above exception, another exception occurred:

EEException                               Traceback (most recent call last)
EEException: Computed value is too large.

During handling of the above exception, another exception occurred:

Exception                                 Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/geemap/common.py](https://localhost:8080/#) in zonal_stats(in_value_raster, in_zone_vector, out_file_path, stat_type, scale, crs, tile_scale, return_fc, verbose, timeout, proxies, **kwargs)
   7039             ee_export_vector(result, filename, timeout=timeout, proxies=proxies)
   7040     except Exception as e:
-> 7041         raise Exception(e)
   7042 
   7043 

Exception: Computed value is too large.

[giswqs]

The limit is enforced by Earth Engine, not by geemap. It doesn't matter if you are using JS or Python. The solution is to use a collection with fewer images

[ambarja]

Thank you very much Dr. Wu