title: Pandas merge columns if 'NaN' value is present in one line code
body: <p>My dataset <code>df</code> looks like this:</p>
  
  <pre><code>time         high      low     offset
  2017-01-01   1.012     0.921    NaN
  2017-01-02   1.019     0.934    NaN 
  2017-01-03   1.213     NaN      0.982
  2017-01-04   1.112     0.965    NaN
  </code></pre>
  
  <p>here, either <code>low</code> value is <code>NaN</code> or <code>offset</code> value is <code>NaN</code> but not both</p>
  
  <p>I want to create a new column called <code>low_offset_merge</code></p>
  
  <p>so that <code>low_offset_merge</code> will contain the merged values of <code>low</code> and <code>offset</code> and it will all have a <code>number</code> value and no <code>NaN</code>, like below:</p>
  
  <pre><code>time         high      low     offset  low_offset_merge
  2017-01-01   1.012     0.921    NaN       0.921
  2017-01-02   1.019     0.934    NaN       0.934
  2017-01-03   1.213     NaN      0.982     0.982
  2017-01-04   1.112     0.965    NaN       0.965
  </code></pre>
  
  <p>What did I do? </p>
  
  <pre><code>- First, check if `low` has `NaN` values and set the value     
  df.loc[df['low'] != 'NaN', 'low_offset_merge'] = df['offset']
  
  - Second, fill in the `NaN` column
  df['low_offset_merge'] = df['low_offset_merge'].fillna(value=df['offset'])
  </code></pre>
  
  <p>I am looking for a one-line solution, can you please help?</p>