title: pandas dropna drops more than isna counts
body: <p>I've got a 3-column dataset with 7100 rows.</p>
  <p><code>data.isna().sum()</code> shows, that one column contains 117 NaN vlaues, the others 0.
  <code>data.isnull().sum()</code> shows also 117 for one and 0 for the other columns.</p>
  <p><code>data.dropna(inplace=True)</code> drops 351 rows. Can anyone explain this to me? Am I doing anything wrong?</p>
  <p>Edit:</p>
  <p>I now examined the deleted rows. There are 351 rows deleted, where <code>dropped.isna().sum().sum()</code> shows a total of 117 NaN values.</p>
  <p><code>dropped[~dropped['description'].isna()]</code> shows an empty table. So the result seems to be correct as far as I can see.</p>
  <p>Now I'm just curious how the difference in counting occurs.</p>
  <p>Sadly I'm not able/allowed to provide a data sample.</p>