title: Different std in pandas vs numpy
body: <p>The standard deviation differs between pandas and numpy. Why and which one is the correct one? (the relative difference is 3.5% which should not come from rounding, this is high in my opinion).</p>
  <p><strong>Example</strong></p>
  <pre><code>import numpy as np
  import pandas as pd
  from StringIO import StringIO
  
  a='''0.057411
  0.024367
   0.021247
  -0.001809
  -0.010874
  -0.035845
  0.001663
  0.043282
  0.004433
  -0.007242
  0.029294
  0.023699
  0.049654
  0.034422
  -0.005380'''
  
  
  df = pd.read_csv(StringIO(a.strip()), delim_whitespace=True, header=None)
  
  df.std()==np.std(df) # False
  df.std() # 0.025801
  np.std(df) # 0.024926
  
  (0.024926 - 0.025801) / 0.024926 # 3.5% relative difference
  </code></pre>
  <p>I use these versions:</p>
  <pre><code>pandas '0.14.0'
  numpy '1.8.1'
  </code></pre>