title: panda reads 0.6 as 0.59999999999999998 - wrong decimal places
body: <p>Via panda the values in the table below are read with non existing decimal place e.g.: 0.6 is read as 0.59999999999999998 (see code below)</p>
  
  <p>I would have expected to read 0.6 as 0.6.</p>
  
  <p>Why is it interpreted like this and what do I have to code to get the expected behaviour?</p>
  
  <pre><code>ldcSc = pd.read_csv(os.path.join(basepath, 'kmod_table.csv'), skiprows=2)
  ldcSc
  
      LDC             1        2        3
  0   permanent      0.6      0.6     0.50
  1   long-term      0.7      0.7     0.55
  2   medium-term    0.8      0.8     0.65
  3   short-term     0.9      0.9     0.70
  4   instantaneous  1.1      1.1     0.90
  
  print(ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'permanent'].index[0]), '2'))
  print(ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'short-term'].index[0]), '1'))
  print(ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'medium-term'].index[0]), '3'))
  </code></pre>
  
  <p>prints to: 
  0.6
  0.9
  0.65</p>
  
  <p>BUT:</p>
  
  <pre><code>ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'permanent'].index[0]), '2')
  </code></pre>
  
  <p>0.59999999999999998</p>
  
  <pre><code>ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'short-term'].index[0]), '1')
  </code></pre>
  
  <p>0.90000000000000002</p>
  
  <pre><code>ldcSc.get_value((ldcSc.LDC[ldcSc.LDC == 'medium-term'].index[0]), '3')
  </code></pre>
  
  <p>0.65000000000000002</p>