title: Using usecols and skiprows at the same time (in Pandas read_csv) gives error
body: <p>I am using read_csv in Pandas v0.18.1 to read in some data. I want to choose a subset of columns and rows from the csv, so I have tried:</p>
  
  <pre><code>df_a = pd.read_csv(filepath, index_col = False, usecols=cols_to_use, skiprows=1)
  </code></pre>
  
  <p>This gives me a <em>ValueError: Usecols do not match names.</em>
  Note that cols_to_use is a list of column names, but if I leave out the skiprows part:</p>
  
  <pre><code>df_a = pd.read_csv(filepath, index_col = False, usecols=cols_to_use)
  </code></pre>
  
  <p>it works fine, and similarly if I leave out the usecols bit and put skiprows back in, that works fine too.</p>
  
  <p>Could this be a bug (that you can't use usecols and skiprows at the same time)? I've tried looking in the documentation but couldn't find any mention of it. Or perhaps there is a logical reason that you can't use both?</p>
  
  <p>(Also if there is a better/more obvious way of picking out a subset of columns and rows from a csv that would be appreciated too!)</p>
  
  <p>Thanks in advance!</p>