title: How to store months from NETcdf time dimension (0 corresponding to jan)?
body: <p>I have a 3d NETcdf dataset and am trying to work with the precipitation variable. I would like to plot the monthly averages of it over 60 years, but am having difficulty producing a plot that is consistent with previous averaging calculations I did not involving for loops. Here is how I store the values for the january, february and take the mean:</p>
  
  <pre><code>janNES = np.empty_like(conprecip[0:720,6:-11,95:141])
  
  for i in range(0,720,12):
       janNES[i]=(NESprecip[i,6:-11,95:141])          
  
  mjanNES=(np.mean(janNES, axis=0))
  
  febNES = np.empty_like(conprecip[0:720,6:-11,95:141])
  
  for i in range(1,720,12):
       febNES[i]=(NESprecip[i,6:-11,95:141]) 
  
  mfebNES=(np.mean(febNES, axis=0))
  
  #values that are plotted, monthly 60 year averages
  np.mean(mjanNES-mjan)
  np.mean(mfebNES-mfeb)
  </code></pre>
  
  <p>Where 0-11 is jan to dec, so I store values from the other months similarly. I believe there is something wrong with the way I am storing the data as its producing weird results after I subtract the control(mjan and mfeb, store using this method) and take the mean again. Thank you for reading and helping.</p>