title: Pandas read csv file with float values results in weird rounding and decimal digits
body: <p>I have a csv file containing numerical values such as <code>1524.449677</code>. There are always exactly 6 decimal places.</p>
  
  <p>When I import the csv file (and other columns) via pandas <code>read_csv</code>, the column automatically gets the datatype <code>object</code>. My issue is that the values are shown as <code>2470.6911370000003</code> which actually should be <code>2470.691137</code>. Or the value <code>2484.30691</code> is shown as <code>2484.3069100000002</code>.</p>
  
  <p>This seems to be a datatype issue in some way. I tried to explicitly provide the data type when importing via <code>read_csv</code> by giving the <code>dtype</code> argument as <code>{'columnname': np.float64}</code>. Still the issue did not go away.</p>
  
  <p>How can I get the values imported and shown exactly as they are in the source csv file?</p>