title: python pandas date_range when importing with read_csv
body: <p>I have a .csv file with some data in the following format:</p>
  
  <pre><code>1.69511909,  0.57561167,  0.31437427,  0.35458831,  0.15841189, 0.28239582, -0.18180907,  1.34761404, -1.5059083,  1.29246638
  -1.66764664,  0.1488095,  1.03832221, -0.35229205,  1.35705861, -1.56747104, -0.36783851, -0.57636948,  0.9854391,  1.63031066
  0.87763775,  0.60757153,  0.64908314, -0.68357724,  0.33499838, -0.08557089,  1.71855596, -0.61235066, -0.32520105,  1.54162629
  </code></pre>
  
  <p>Every line corresponds to a specific day, and every record in a line corresponds to a specific hour in that day.</p>
  
  <p>Is there is a convenient way of importing the data with <code>read_csv</code> such that everything would be correctly indexed, i.e. the importing function would discriminate different days (lines), and hours within days (separate records in lines).</p>