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Due to a large NetCDF4 file, I get a MemoryError when I want to transform it into Pandas dataframe. But I don't need everything from the netCDF4 file, so I wanted to know if I could cut the file priorly, and after transforming into dataframe

My file looks like this: enter image description here

xr is for the xarray library Time variable contains all hours from 2019-01-01 to 2019-01-31 Unfortunately I can't filter on Copernicus website but I only need time at 09:00:00

Do you know how I could do it? Using xarray library or other way.

Thanks

ImFabien75
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1 Answers1

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You can use sel to filter your dataset:

import pandas as pd
import xarray as xr
import datetime

# Load a demo dataset
ds = xr.tutorial.load_dataset('air_temperature')

# Keep only 12:00 rows
df = ds.sel(time=datetime.time(12)).to_dataframe()

Output:

>>> df
                                       air
lat  time                lon              
75.0 2013-01-01 12:00:00 200.0  242.299988
                         202.5  242.199997
                         205.0  242.299988
                         207.5  242.500000
                         210.0  242.889999
...                                    ...
15.0 2014-12-31 12:00:00 320.0  296.889984
                         322.5  296.589996
                         325.0  295.690002
                         327.5  295.489990
                         330.0  295.190002

[967250 rows x 1 columns]
Corralien
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