title: conditional row read of csv in pandas
body: <p>I have large CSVs where I'm only interested in a subset of the rows.  In particular, I'd like to read in all the rows which occur before a particular condition is met.</p>
  
  <p>For example, if <code>read_csv</code> would yield the dataframe:</p>
  
  <pre><code>     A    B      C
  1   34   3.20   'b'
  2   24   9.21   'b'
  3   34   3.32   'c'
  4   24   24.3   'c'
  5   35   1.12   'a'
  ... 
  1e9 42   2.15   'd'
  </code></pre>
  
  <p>is there some way to read all the rows in the csv until col B exceeds 10.  In the above example, I'd like to read in:</p>
  
  <pre><code>     A    B      C
  1   34   3.20   'b'
  2   24   9.21   'b'
  3   34   3.32   'c'
  4   24   24.3   'c'
  </code></pre>
  
  <p>I know how to throw these rows out once I've read the dataframe in, but at this point I've already spent all that computation reading them in.  I do not have access to the index of the final row before reading the csv (no <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html" rel="noreferrer">skipfooter</a> please)</p>