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Full documentation on NetCDF functionality in Metview is here. |
Setup
Navigate into the 4_netcdf folder within Metview where you will find some data files and other icons.
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You will need to tell Metview how to visualise this data, as there are multiple variables. Create a new NetCDF Visualiser icon, edit it and set the following parameters:
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Save the icon and visualise it. For fun, drop the supplied icons contour_t2m and mollweide into the plot window to obtain the following:
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Have a look in the solutions folder and edit and run the script netcdf_to_pandas.py. This shows how to extract some metadata from the previous netCDF file, and also some value arrays and convert into a pandas dataframe. The code is also here:
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import metview as mv import pandas as pd nc = mv.read("madis-maritime.nc") # print some global fields print('Variables: \n', nc.variables()) print('Global attributes: \n', nc.global_attributes()) # extract certain variables - setcurrent() followed by values() nc.setcurrent('latitude') lats = nc.values() nc.setcurrent('longitude') lons = nc.values() nc.setcurrent('temperature') temps = nc.values() print('temperature attributes: \n', nc.attributes()) # create a dictionary in order to convert to pandas pddict = {'latitude' : lats, 'longitude' : lons, 'temperature' : temps} df = pd.DataFrame(pddict) print('Dataframe: \n', df) print('temperature describe: \n', df.temperature.describe()) |