title: Pandas - dropping rows with missing data not working using .isnull(), notnull(), dropna()
body: <p>This is really weird. I have tried several ways of dropping rows with missing data from a pandas dataframe, but none of them seem to work.
  This is the code (I just uncomment one of the methods used - but these are the three that I used in different modifications - this is the latest):</p>
  
  <pre><code>import pandas as pd
  Test = pd.DataFrame({'A':[1,2,3,4,5],'B':[1,2,'NaN',4,5],'C':[1,2,3,'NaT',5]})
  print(Test)
  #Test = Test.ix[Test.C.notnull()]
  #Test = Test.dropna()
  Test = Test[~Test[Test.columns.values].isnull()]
  print "And now"
  print(Test)
  </code></pre>
  
  <p>But in all cases, all I get is this:</p>
  
  <pre><code>   A    B    C
  0  1    1    1
  1  2    2    2
  2  3  NaN    3
  3  4    4  NaT
  4  5    5    5
  And now
     A    B    C
  0  1    1    1
  1  2    2    2
  2  3  NaN    3
  3  4    4  NaT
  4  5    5    5
  </code></pre>
  
  <p>Is there any mistake that I am making? or what is the problem? Ideally, I would like to get this:</p>
  
  <pre><code>   A    B    C
  0  1    1    1
  1  2    2    2
  4  5    5    5
  </code></pre>