Value NAN in NetCDF4 file for lat&lon using Python

Question

I have two files in NetCDF4 (latlon and other file without latlon).

I open the two files in the same code and I choose one variable and the two variable lon and lat. When I write lon I have the value nan and I don't know why.

The two files have same dimensions (size) and same dimensions for variables all I need is to show the value of lat&lon when I open the two files. How can I do it?

In [54]: import numpy as np
    ...: import netCDF4
    ...: 
    ...: 
    ...: fic1='/data/latlon_+000.0_globe.nc'
    ...: 
    ...: nc1 = netCDF4.Dataset(fic1,'r')
    ...: 
    ...: lon = nc1.variables['lon'][:]
    ...: lat = nc1.variables['lat'][:]
    ...: 
    ...: fic='/data/Mmultic3kmNC4_msg04_201905080200
    ...: .nc'
    ...: 
    ...: 
    ...: nc = netCDF4.Dataset(fic,'r')
    ...: IR=nc.variables['IR_108'][:]
    ...: 
    ...: 


In [55]: 

In [55]: lon
Out[55]: 
masked_array(
  data=[[nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        ...,
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan]],
  mask=False,
  fill_value=1e+20,
  dtype=float32)

In [56]: lat
Out[56]: 
masked_array(
  data=[[nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        ...,
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan]],
  mask=False,
  fill_value=1e+20,
  dtype=float32)

In [57]: 

How I can get value of lat & lon?

Answer 1

after checking the contents of the 2 files, there seems to be a problem with the dimensions of the one with lat lon variables since the attribute current_shape = (3712, 3712) for lat and lon while it should be (3712,).

The file may be corrupted and you'll have to create it again from the X and Y attributes of the second file since they are linked.

to do so you can start with this answer , you will also need to transform the projected coordinates to lat lon, and for that you can use pyproj