title: pd.read_csv gives me str but need float
body: <p>I have a CSV which looks like this:</p>
  
  <pre><code>Date,Open,High,Low,Close,Adj Close,Volume
  2007-07-25,4.929000,4.946000,4.896000,4.904000,4.904000,0
  2007-07-26,4.863000,4.867000,4.759000,4.777000,4.777000,0
  2007-07-27,4.741000,4.818000,4.741000,4.788000,4.788000,0
  2007-07-30,4.763000,4.810000,4.763000,4.804000,4.804000,0
  </code></pre>
  
  <p>after</p>
  
  <pre><code>data = pd.read_csv(file, index_col='Date').drop(['Open','Close','Adj Close','Volume'], axis=1)
  </code></pre>
  
  <p>i end up with a df which looks like this:</p>
  
  <pre><code>                High       Low
  Date                          
  2007-07-25  4.946000  4.896000
  2007-07-26  4.867000  4.759000
  2007-07-27  4.818000  4.741000
  2007-07-30  4.810000  4.763000
  2007-07-31  4.843000  4.769000
  </code></pre>
  
  <p>Now i want to get High - Low. Tried:</p>
  
  <pre><code>np.diff(data.values, axis=1)
  </code></pre>
  
  <p>but getting an error: unsupported operand type(s) for -: 'str' and 'str'</p>
  
  <p>but sure why the values in the df are str in the first place. Grateful for any solution.</p>