title: why dropna() is not working as I expect it to?
body: <p>I have asked this question already once but deleted it because it did not address the issue in the correct way.</p>
  
  <p>I want to drop all rows that contain <code>NaN</code>. I am quite sure I would need to apply </p>
  
  <pre><code>df.dropna(how='all', inplace=True)
  </code></pre>
  
  <p>to achieve what I need. But for some unknown reason it simply does not work. I even have the suspicion that it's a software/version related issue. I am working with anaconda and pandas 0.18.0 and conda version  conda version : 4.1.2
    conda-build version : 1.19.0
         python version : 3.5.1.final.0
       requests version : 2.9.1</p>
  
  <p>I create a data frame from csv with following:</p>
  
  <pre><code>df1 = pd.read_csv('Vols.csv', sep=',', parse_dates=True, 
  index_col="Date",usecols=['Date','60DAY_IMPVOL'])
  df2 = pd.read_csv('DAX02072016.csv', sep=',', index_col= "Date", parse_dates=True,
  usecols=['Date','Close'])
  df = pd.concat([df1, df2], axis=1)
  </code></pre>
  
  <p>What I get is a data frame:</p>
  
  <pre><code>         60DAY_IMPVOL        Close
  Date
  2004-02-03     NaN            4057.510010
  2004-02-04     NaN            4028.370117
  2004-02-05     NaN            4014.790039
  2004-02-06     18.54          4044.989990
  2004-02-09     17.76          4098.970215
  2004-02-10     NaN            4077.635363
  </code></pre>
  
  <p>and applying dropna() does not make anything, also when I use axis=1 or axis=0. So anyone any suggestion what could be the reason why it's not working?</p>