title: Pandas read_csv speed up
body: <p>I am reading a large csv which has around 10 million rows and 20 different columns (with header names).</p>
  
  <p>I have values, 2 columns with dates and some string.</p>
  
  <p>Currently it takes me around 1.5 minutes to load the data with something like this:</p>
  
  <pre><code>df = pd.read_csv('data.csv', index_col='date', parse_dates = 'date')
  </code></pre>
  
  <p>I want to ask, how can I make this significantly faster yet, have same dataframe once reading data.</p>
  
  <p>I tried using HDF5 database, but it was just as slow. </p>
  
  <p>Subset of the data I am trying to read (I chose 8 columns and gave 3 rows out of actual 20 columns and couple million rows):</p>
  
  <pre><code>Date    Comp     Rating Price   Estprice    Dividend?   Date_earnings   Returns
  3/12/2017   Apple   Buy   100   114              Yes    4/4/2017    0.005646835
  3/12/2017   Blackberry  Sell    120 97            No    4/25/2017   0.000775331
  3/12/2017   Microsoft   Hold    140 100          Yes    5/28/2017   0.003028423
  </code></pre>
  
  <p>Thanks for the advice.</p>