title: Ignoring non-numerical string values in pandas dataframe
body: <p>I have a DataFrame in which a column might have three kinds of values, integers (12331), integers as strings ('345') or some other string ('text').</p>
  
  <p>Is there a way to drop all rows with the last kind of string from the dataframe, and convert the first kind of string into integers? Or at least some way to ignore the rows that cause type errors if I'm summing the column.</p>
  
  <p>This dataframe is from reading a pretty big CSV file (25 GB), so I'd like some solution that would work when reading in chunks.</p>