title: Create new dataFrame based on reformatted columns from old dataFrame
body: <p>I imported the data from a database</p>
  
  <pre><code>df = spark.read.format("com.mongodb.spark.sql.DefaultSource").option("uri",
  "mongodb://127.0.0.1/test.db").load()
  </code></pre>
  
  <p>I have selected the double columns using</p>
  
  <pre><code>double_list = [name for name,types in df.dtypes if types == 'double']
  </code></pre>
  
  <p>Credits to @Ramesh Maharjan.
  To remove special characters we use</p>
  
  <pre><code>removedSpecials = [''.join(y for y in x if y.isalnum()) for x in double_list]
  </code></pre>
  
  <p>The question is:</p>
  
  <p>How can I create a new dataframe based on <code>df</code> with ONLY <code>double_list</code> columns. ?</p>