title: pyspark replace multiple values with null in dataframe
body: <p>I have a dataframe (<code>df</code>) and within the dataframe I have a column <code>user_id</code></p>
  <pre class="lang-python prettyprint-override"><code>df = sc.parallelize([(1, &quot;not_set&quot;),
                       (2, &quot;user_001&quot;),
                       (3, &quot;user_002&quot;),
                       (4, &quot;n/a&quot;),
                       (5, &quot;N/A&quot;),
                       (6, &quot;userid_not_set&quot;),
                       (7, &quot;user_003&quot;),
                       (8, &quot;user_004&quot;)]).toDF([&quot;key&quot;, &quot;user_id&quot;])
  </code></pre>
  <p>df:</p>
  <pre class="lang-python prettyprint-override"><code>+---+--------------+
  |key|       user_id|
  +---+--------------+
  |  1|       not_set|
  |  2|      user_003|
  |  3|      user_004|
  |  4|           n/a|
  |  5|           N/A|
  |  6|userid_not_set|
  |  7|      user_003|
  |  8|      user_004|
  +---+--------------+
  </code></pre>
  <p>I would like to replace the following values: <code>not_set</code>, <code>n/a</code>, <code>N/A</code> and <code>userid_not_set</code> with null.</p>
  <p>It would be good if I could add any new values to a list and they to could be changed.</p>
  <p>I am currently using a CASE statement within <strong>spark.sql</strong> to preform this and would like to change this to pyspark.</p>