title: Python: which is the best way to read large .csv file?
body: <p>I have to read large <code>.csv</code> of around <code>20MB</code>. Those files are tables composed by <code>8</code> columns and <code>5198</code> rows. I have to do some statistics over a specific column <code>I</code>.</p>
  
  <p>I have <code>n</code> different files and this what I am doing:</p>
  
  <pre><code>stat = np.arange(n)
      I = 0
      for k in stat:
          df = pd.read_csv(pathS+'run_TestRandom_%d.csv'%k, sep=' ')
          I+=df['I']
      I = I/k ## Average
  </code></pre>
  
  <p>This process takes <code>0.65s</code> and I wondering if there is a fastest way.</p>