title: Pandas compare two columns and copy value of another column if there is a match only for first unique value
body: <p>I have two different dataframes of which I want to compare two columns. If the value of the first dataframe appears anywhere in the column of the second dataframe, I want to copy the value next to the matching value and copy this to a new column in the first dataframe.</p>
  
  <p>The dataframes look like this:</p>
  
  <p>DF1 </p>
  
  <pre><code>╔═══════════════════╗
  ║       Email       ║
  ╠═══════════════════╣
  ║ Johndoe@gmail.com ║
  ║ janedoe@gmail.com ║
  ║ foo@gmail.com     ║
  ║ foobar@gmail.com  ║
  ║ bar@gmail.com     ║
  ╚═══════════════════╝
  </code></pre>
  
  <p>DF2</p>
  
  <pre><code>╔════════════════════╦═════════════╗
  ║       Email        ║    Phone    ║
  ╠════════════════════╬═════════════╣
  ║ Johndoe@gmail.com  ║ 111-111-111 ║
  ║ Johndoe@gmail.com  ║ 111-111-111 ║
  ║ Johndoe@gmail.com  ║ 111-111-111 ║
  ║ Jakedoe@gmail.com  ║ 123-123-123 ║
  ║ jamesdoe@gmail.com ║ 321-321-321 ║
  ║ janedoe@gmail.com  ║ 222-222-222 ║
  ║ janedoe@gmail.com  ║ 222-222-222 ║
  ║ foo@gmail.com      ║ 333-333-333 ║
  ║ foobar@gmail.com   ║ 444-444-444 ║
  ║ foobar@gmail.com   ║ 444-444-444 ║
  ║ bar@gmail.com      ║ 555-555-555 ║
  ╚════════════════════╩═════════════╝
  </code></pre>
  
  <p>The output should look like this:</p>
  
  <pre><code>╔═══════════════════╦═════════════╗
  ║       email       ║    phone    ║
  ╠═══════════════════╬═════════════╣
  ║ Johndoe@gmail.com ║ 111-111-111 ║
  ║ janedoe@gmail.com ║ 222-222-222 ║
  ║ foo@gmail.com     ║ 333-333-333 ║
  ║ foobar@gmail.com  ║ 444-444-444 ║
  ║ bar@gmail.com     ║ 555-555-555 ║
  ╚═══════════════════╩═════════════╝
  </code></pre>
  
  <p>I've tried looping over the column in DF1 and comparing every value to the corresponding column in DF2 but it also returns the duplicates. </p>
  
  <p>What would be a good way to accomplish this with Pandas? </p>
  
  <p>Thanks!</p>