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I am doing a number of calculations on a timeseries of data and want to create a 2d netcdf file with the results of those calculations.

However, when saving the calculated values in the new array I get the following message:

IndexError: too many indices for array.

I am using python 3.6 with the NetCDF4 and numpy libraries.

val_list=[]
av_array=[]
#create netcdf
out_file=netCDF4.Dataset("test.nc","w", format="NETCDF4")
tempgrp=out_file.createGroup(var)
tempgrp.createDimension('lon', 575)
tempgrp.createDimension('lat', 541)
tempgrp.createDimension('time', None)
            
longitude = tempgrp.createVariable('Longitude', 'f4', 'lon')
latitude = tempgrp.createVariable('Latitude', 'f4', 'lat')  
temp = tempgrp.createVariable(var, 'f4', ('time', 'lon', 'lat'))
time = tempgrp.createVariable('Time', 'i4', 'time')
          
longitude[:] = 575
latitude[:] = 541

for i in range(540):
    for j in range(574):
                del val_list
                val_list=[]
                for t in range(30):
                    #create list of i,j coordinate
                    val_list.append(data[t,0,i,j])
                    #calculations
                av=sum(val_list)/float(len(val_list))#example
                temp[0,j,i] = av #this is where the error occurs

This is the output of print(temp):

<class 'netCDF4._netCDF4.Variable'> float32 Chlx(time, lon, lat) path = /Chlx unlimited dimensions: time current shape = (0, 575, 541) filling on, default _FillValue of 9.969209968386869e+36 used

The idea is to in the end create a 3d array (that is why the time dimension is there).

Can anyone give me a hint to why I get this index error?

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It turns out the netCDF4 library gets an index error if you try to insert a NaN value. I have some areas in the map that are on land and thus have no value. I avoided the issue by adding the following check:

if av == int:
 temp[0,j,i] = av
else:
 temp[0,j,i] = 9.969209968386869e+36

Now when av is a non value it is replaced by the fill value of the netCDF before iserting it. There might be a more ellegant solution but this seems to work for me.

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