title: vlookup equivalent to join 2 tables using pandas
body: <h3>Scenario:</h3>
  
  <ul>
  <li>df1 has all possible auction ID values</li>
  <li>df2 has a subset of possible auction ID values</li>
  <li>df2 contains the object ID present in the auction (can be 0 or positive int)</li>
  </ul>
  
  <h3>Goal:</h3>
  
  <p>Create a new df1 column "object_id" populated with corresponding values in df2</p>
  
  <h3>Example...</h3>
  
  <pre><code>df1 = pd.DataFrame(columns=['auction_id'], data=[1,2,3,4,5,6,7,8,9])
  
  auction_id
  1  
  2  
  3  
  4  
  5  
  6  
  7  
  8  
  9  
  
  
  df2 = pd.DataFrame({'auction_id':[1,2,4,6,7,8,9], 'object_id': [640,0,332,332,0,58,332]})
  
  auction_id  object_id  
  1             640  
  2             0  
  4             332  
  6             332  
  7             0  
  8             58  
  9             332  
  </code></pre>
  
  <h3>My best effort so far</h3>
  
  <p>using <a href="https://stackoverflow.com/questions/25493625">vlookup in Pandas using join</a>):</p>
  
  <pre><code>df1['object_id'] = df1.auction_id.map(df2.object_id)
  </code></pre>
  
  <p>Which yields:</p>
  
  <pre><code>df1  
  auction_id  object_id
  1             0  
  2             332  
  3             332  
  4             0  
  5             58  
  6             332  
  7             NaN  
  8             NaN  
  9             NaN  
  </code></pre>