title: How to extract non NA values in a list or dict from a pandas dataframe
body: <p>I have a df like this,</p>
  
  <p>df,</p>
  
  <pre><code>    AAA BBB CCC
  0   4   10  100
  1   5   20  50
  2   6   30  -30
  3   7   40  -50
  </code></pre>
  
  <p><code>df_mask = pd.DataFrame({'AAA' : [True] * 4, 'BBB' : [False] * 4,'CCC' : [True,False] * 2})</code>
  and <code>df.where(df_mask)</code> is</p>
  
  <pre><code>    AAA BBB CCC
  0   4   NaN 100.0
  1   5   NaN NaN
  2   6   NaN -30.0
  3   7   NaN NaN
  </code></pre>
  
  <p>I am trying to extract the non null values like this.</p>
  
  <p>I tried,
       <code>df[df.where(df_mask).notnull()].to_dict()</code> but it gives all the values</p>
  
  <p>My expected output is, </p>
  
  <pre><code>{'AAA': {0: 4, 1: 5, 2: 6, 3: 7},
   'CCC': {0: 100.0, 2: -30.0}}
  </code></pre>