title: Removing data with a non-numeric column value in R
body: <p>So I have a dataset that includes the lung capacity of certain individuals. I am trying to analyze the data distributions and relations. The only problem is that the data is somewhat incomplete. Some of the rows include "N/A" as the lung capacity. This is causing an issue because it is resulting in a mean and sd of always "N/A" for the different subsets. How would I form this into a subset so that it only includes the data that isn't N/A? </p>
  
  <p>I've tried this:</p>
  
  <pre><code>fData1 = read.table("lung.txt",header=TRUE)
  fData2= fData1[fData1$fev!="N/A"]
  </code></pre>
  
  <p>but this gives me an "undefinied columns selected error".</p>
  
  <p>How can I make it so that I have a data set that excludes the rows with "N/A"?</p>
  
  <p>Here is the begining of my data set:</p>
  
  <pre><code> id age    fev height male smoke 
    1  72 1.2840   66.5    1     1
    2  81 2.5530   67.0    0     0
    3  90 2.3830   67.0    1     0
    4  72 2.6990   71.5    1     0
    5  70 2.0310   62.5    0     0
    6  72 2.4100   67.5    1     0
    7  75 3.5860   69.0    1     0
    8  75 2.9580   67.0    1     0
    9  67 1.9160   62.5    0     0
   10  70     NA   66.0    0     1
  </code></pre>