title: Understanding R - is.na and blank "" cells
body: <p>I have a dataset.  Previous to a lot of different file manipulations, many cells were "NA"</p>
  
  <p>After the manipulations, for whatever reason, they have all become just purely empty.  So, to be clear, the SAME cells that were previously NA in excel now just show up totally blank.  No big deal, right?</p>
  
  <p>Well, when I read the data into R I get...</p>
  
  <pre><code> [1] ""                  ""                  "6.4019975396e+17" 
   [4] ""                  ""                  ""                 
   [7] ""                  ""                  "6.40275087015e+17"
  [10] "6.4062774821e+17"  ""                  "6.40602341e+17"   
  [13] ""                  ""                  "6.40360673735e+17"
  [16] "6.40326194081e+17" "6.40326465381e+17" "6.40322363352e+17"
  </code></pre>
  
  <p>Still seems fine to me, except when I run</p>
  
  <p>is.na(data_frame$column_name)</p>
  
  <p>I get ALL FALSE.  Every single one.  Am I misunderstanding how is.na works? </p>
  
  <p>EDIT - This was kind of vague. Of course I am misunderstanding how it works.  Can you explain why an empty cell does not count as an NA cell?  Is there a quick-fix that can be applied to a data frame to make anything that is "" or what would be a blank cell in a CSV to NA for R's sake? </p>