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: 2022-01-15
array(['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)