title: Deleting specific rows from a data frame
body: <p>I am working with some US govt data which has a lengthy list of cities and zip codes.
  After some work, the data is in the following format.</p>
  
  <pre><code>dat1 = data.frame(keyword=c("Bremen", "Brent", "Centreville, AL", "Chelsea, AL", "Bailytown, Alabama", "Calera, Alabama",
                "54023", "54024"), tag=c(rep("AlabamCity",2), rep("AlabamaCityST",2), rep("AlabamaCityState",2), rep("AlabamaZipCode",2)))
  dat1
  </code></pre>
  
  <p>However, there are certain keywords which aren't properly working. So in the below example, there are two 'zip codes' which
  are labeled as 'AlabamaCity' and 'AlabamaCityState'. For some reason, the original data set from the government has several zipcodes
  which aren't properly grouped with the other zip codes.</p>
  
  <pre><code>dat2 = data.frame(keyword=c("Bremen", "Brent", "50143", "Chelsea, AL", "Bailytown, Alabama", "52348",
                "54023", "54024"), tag=c(rep("AlabamCity",2), rep("AlabamaCityST",2), rep("AlabamaCityState",2), rep("AlabamaZipCode",2)))
  dat2
  </code></pre>
  
  <p>I wanted to know how I could iterate through the entire list of keywords and delete all the rows with numeric values (they're acctually saved as character
  values) which don't have a 'AlabamaZipCode' tag. So the previous data should end up looking like.</p>
  
  <pre><code>dat3 = data.frame(keyword=c("Bremen", "Brent", "Chelsea, AL", "Bailytown, Alabama", "54023", "54024"), 
            tag=c(rep("AlabamCity",2), rep("AlabamaCityST",1), rep("AlabamaCityState",1), rep("AlabamaZipCode",2)))
  dat3
  </code></pre>
  
  <p>The challange seems to be that there are certain numeric values which I want to keep and others which I want to delete.
  Can anyone help.</p>