title: Importing and combining multiple CSV files in R with differing numbers and names of rows
body: <p>I have a folder with a couple hundred .csv files that I'd like to import and merge. 
  Each file contains two columns of data, but there are different numbers of rows, and the rows have different names. The columns don't have names (For this, let's say they're named <code>x</code> and <code>y</code>).</p>
  
  <p>How can I merge these all together? I'd like to just stick the <code>x</code> columns together, side-by-side, rather than matching on any criteria so that the first row is matched across all data sets and empty rows are given NA. 
  I'd like column <code>x</code> to go away.
  Although, the rows should stay in the order they were originally in from the csv.</p>
  
  <p>Here's an example:</p>
  
  <pre><code>Data frame 112_c1.csv:
  
  x       y
  1  -0.5604
  3  -0.2301
  4   1.5587
  5   0.0705
  6   0.1292
  
  
  Dataframe 112_c2.csv:
  
  x         y
  2   -0.83476
  3   -0.82764
  8    1.32225
  9    0.36363
  13   0.9373
  42  -1.5567
  50  -0.12237
  51  -0.4837
  
  Dataframe 113_c1.csv:
  
  x       y
  5   1.5783
  6   0.7736
  9   0.28273
  15  1.44565
  23  0.999878
  29 -0.223756
  =
  
  Desired result
  
  112_c1.y   112_c2.y  113_c1.y
  -0.5604   -0.83476   1.5783
  -0.2301   -0.82764   0.7736
  1.5587     1.32225   0.28273
  0.0705     0.36363   1.44565
  0.1292     0.9373    0.999878
  NA        -1.5567    -0.223756
  NA        -0.12237   -0.223756
  NA        -0.12237   NA
  NA        -0.4837    NA
  </code></pre>
  
  <p>I've tried a few things, and looked through many other threads. But code like the following simply produces NAs for any following columns: </p>
  
  <pre><code>df &lt;- do.call(rbind.fill, lapply(list.files(pattern = "*.csv"), read.csv))
  </code></pre>
  
  <p>Plus, if I use <code>rbind</code> instead of <code>rbind.fill</code> I get the error that <code>names do not match previous names</code> and I'm unsure of how to circumvent this matching criteria. </p>