title: Fastest Way to Iterate Over Dataframe Column to Find Match in Strings
body: <p>Here's a very truncated extract from a large dataframe:</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>name</th>
  <th>age</th>
  <th>city</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>ben</td>
  <td>66</td>
  <td>NY</td>
  </tr>
  <tr>
  <td>rob</td>
  <td>45</td>
  <td>LON</td>
  </tr>
  <tr>
  <td>james</td>
  <td>22</td>
  <td>LA</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>I also have a numerous strings that each contain different words but will contain one (not more) of the values in the name column.</p>
  <p>For example:</p>
  <ol>
  <li>&quot;rob was born in London&quot;</li>
  <li>&quot;ben once lived in New York&quot;</li>
  </ol>
  <p>For each string I want to iterate over the &quot;name&quot; column to find the name that matches the name in the string and return the age of the person.</p>
  <p>So in the first example the desired result is 45 and in the second example the desired result is 66.</p>
  <p>I am new to Pandas and am struggling. Can anyone point me in the right direction?</p>