title: R tm package DataframeSource import
body: <p>Reading a CSV into R and wanting to make a corpus from it with the tm package, but not getting the desired results. Currently, when I read in a CSV of text, then inspect the corpus, the data is all numerical. (I only included the first three columns of <code>data</code> to protect privacy; there are nine as shown in the inspect results.)</p>
  
  <pre><code>library(tm)
  
  data &lt;- read.csv("filename.csv")
  head(data)    
    Directory.Code First.Name Last.Name
  1        SCA0025     Nbcde    Cdbaace
  2        SCA0025   AJCocei    aiceice
  3        SCA0025      aceca   Ac;eice
  4        SCA0025      Acoicm  aie;cee 
  5        SCA0025     acei     aciomac
  6        SCA0025       caeij   CIMCEv
  
  data.corp &lt;- corpus(DataframeSource,data)
  inspect(data.corp[1])
  A corpus with 1 text document
  
  The metadata consists of 2 tag-value pairs and a data frame
  Available tags are:
    create_date creator 
  Available variables in the data frame are:
    MetaID 
  
  $`1`
  16
  2195
  6655
  6613
  1
  5
  9757
  1
  1
  </code></pre>
  
  <p>If it helps to know the purpose: I am trying to read in a csv of names and un-normalized job titles/descriptions, then compare to a corpus of known titles/descriptions as categories. Now that I type this in, I realize that this csv will be my test/prediction data, but I still want to build a corpus from a csv with colnames = KnownJobTitle,Description.</p>
  
  <p>The goal of this question is to successfully read a CSV into a corpus, but I would also like to know if it is advisable to use the tm package for more than 2 categorizations, and/or if there are other packages more suited to this task.</p>