title: Replacing a multiple strings in a Pandas Series with values from a lookup table df
body: <p>I have a DataFrame like this, where the <code>type</code> column are strings delimited with <code>~</code>:</p>
  
  <pre><code>id | types    |
  ---------------
  1  | A1~B1    |
  2  | B1       |
  3  | A1~A2~B2 |
  </code></pre>
  
  <p>I need to replace the strings in the 'type' column based on a lookup table, shown below, where both columns are strings. While doing this, I need to ensure that the final output has commas between the <code>types</code>.</p>
  
  <pre><code>type | description      |
  ------------------------
  A1   | This is good     |
  A2   | This is OK       |
  B1   | This is not good |
  B2   | This is bad      |
  </code></pre>
  
  <p>So the final output looks like this:</p>
  
  <pre><code>id | types                                 |
  --------------------------------------------
  1  | This is good, This is not good        |
  2  | This is not good                      |
  3  | This is good, This is OK, This is bad |
  </code></pre>
  
  <p>I've read that <code>.map()</code> is a good function to use, but I haven't been able to figure out how I can apply it to this scenario. Thanks in advance.</p>