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  • jibcar · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1135302642 https://github.com/pydata/xarray/issues/2313#issuecomment-1135302642 https://api.github.com/repos/pydata/xarray/issues/2313 IC_kwDOAMm_X85Dq1fy jibcar 54370222 2022-05-24T01:31:22Z 2022-05-24T01:31:22Z NONE

Hello:

I have to find maximum precipitation of each year (for example: 2007 and 2008, Dataset link are: 2007 and 2008). I have done this using resample method (i.e. .resample(time='Y').max()) after concatenating it along time dimension.

Following along SO, I am wondering if I can use preprocess to find maximum (or minimum or average) for each file first and then concatenate it using time dimension. I tried the following code and was not successful. Can someone help me with this?

```import dask.array as da import numpy as np import xarray as xr

from dask.distributed import Client client = Client() client

def preprocess_func(ds): '''Get maximum (or minimum or average) from each file and concatenate along time''' return ds.precip.max('time')

prec_ds=xr.open_mfdataset([prec_2007,prec_2008], chunks={"lat": 25,"lon": 25,"time": -1,}, preprocess=preprocess_func, concat_dim='time')```

 
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   Example on using `preprocess` with `mfdataset` 344614881

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