title: In tensorflow, How to compute mean for each columns of a batch generated from a csv that has NaNs in multiple columns?
body: <p>I am reading in a csv in batches and each batch has nulls in various place. I dont want to use tensorflow transform as it requires loading the entire data in memory. Currently i cannot ignore the NaNs present in each column while computing means if i am to try to do it for the entire batch at once. I can loop through each column and then find the mean per columns that way but that seems to be an inelegant solution. </p>
  
  <p>Can somebody help in finding the right way to compute the mean per column of a csv batch that has NaNs present in multiple columns. Also, <code>[1,2,np.nan]</code> should produce 1.5 not 1.</p>