title: Why is NaT data type not responding as NaN?
body: <p>Here's an example of the original data:</p>
  
  <pre><code>28      22/03/2015
  29      22/03/2015
  30      22/03/2015
  31             NaN
  </code></pre>
  
  <p>I then change the format as follows:</p>
  
  <pre><code>df.loc[2,2:]=pd.to_datetime(df.loc[2,2:]).dt.strftime('%Y-%m-%d')
  </code></pre>
  
  <p>Which gives me this as data:</p>
  
  <pre><code>28     2015-03-22
  29     2015-03-22
  30     2015-03-22
  31            NaT
  </code></pre>
  
  <p>Now when I try to replace NaT (because it gives me errors when uploading it to Postgres), I two different situations:
  1. Nothing changes when I do this:</p>
  
  <pre><code>df.loc[2,]=df.loc[2].fillna('Unknown')
  </code></pre>
  
  <ol start="2">
  <li>All the data changes to "Unknown" when I add "inplace=True":</li>
  </ol>
  
  <pre><code>df.loc[2,]=df.loc[2].fillna('Unknown', inplace=True)
  
  28     None
  29     None
  30     None
  31     None
  </code></pre>
  
  <p>Is this a problem with how I've formatted it? With all other data types fillna works on NaN.</p>