title: NaN results with pandas mean function
body: <p>I try to have the mean of a row in my Python DataFrame, but I get a NaN return for every row.
  Why I get this result and how can I solve that ? </p>
  
  <p>Goog key ratios :
  <a href="http://www.gogofile.com/Default.aspx?p=sc&amp;ID=635118193040317500_6234" rel="noreferrer">http://www.gogofile.com/Default.aspx?p=sc&amp;ID=635118193040317500_6234</a></p>
  
  <pre><code>path = 'GOOG Key Ratios.csv'
  #print(open(path).read())
  data = pd.read_csv(path, skiprows = 2, names = ['Y0','Y1','Y2','Y3','Y4','Y5','Y6','Y7','Y8','Y9','Y10'], index_col = 0)
  noTTM = data.iloc[:,0:10]
  print(data.mean(1))
  grossMargin = noTTM[2:3]
  print(grossMargin.mean(1))
  </code></pre>
  
  <p>Return:</p>
  
  <pre><code>Gross Margin %   NaN
  dtype: float64
  </code></pre>
  
  <p>Regards,</p>