import xarray as xr
ds = xr.open_dataset("pr_hyras_1_2021_v3-0_de.nc")
ds
<xarray.Dataset>
Dimensions: (time: 365, x: 1200, y: 1100)
Coordinates:
* time (time) datetime64[ns] 2021-01-01T18:00:00 ... 2021-12-...
lon (y, x) float32 ...
lat (y, x) float32 ...
* x (x) float64 3.5e+06 3.502e+06 ... 4.698e+06 4.7e+06
* y (y) float64 2.1e+06 2.102e+06 ... 3.198e+06 3.2e+06
Data variables:
crs int32 1
pr (time, y, x) float32 ...
number_of_station (time) float32 2.131e+03 2.131e+03 ... 2.156e+03
Attributes: (12/16)
CDI: Climate Data Interface version 1.9.10 (https:/...
Conventions: CF-1.6
source: surface observation
institution: Deutscher Wetterdienst
project_id: HYRAS_DE
realization: V3.0
... ...
title: gridded_precipitation_dataset_(HYRAS_DE PRE)
references: https://opendata.dwd.de/climate_environment/CD...
CDO: Climate Data Operators version 1.9.10 (https:/...
input_data_status: checked
NCO: netCDF Operators version 4.7.5 (Homepage = htt...
creation_date: 2022-01-15array(['2021-01-01T18:00:00.000000000', '2021-01-02T18:00:00.000000000',
'2021-01-03T18:00:00.000000000', ..., '2021-12-29T18:00:00.000000000',
'2021-12-30T18:00:00.000000000', '2021-12-31T18:00:00.000000000'],
dtype='datetime64[ns]')[1320000 values with dtype=float32]
[1320000 values with dtype=float32]
array([3500500., 3501500., 3502500., ..., 4697500., 4698500., 4699500.])
array([2100500., 2101500., 2102500., ..., 3197500., 3198500., 3199500.])
array(1)
[481800000 values with dtype=float32]
array([2131., 2131., 2131., ..., 2156., 2156., 2156.], dtype=float32)