title: dividing all columns in pyspark SQL
body: <p>I am new to Spark and this might be a straightforward problem. </p>
  
  <p>I have a table in pyspark DF1, with a column name "A" and some other columns. The other column names might change in various cases. I want to generate a table DF2 by dividing the values of these "other" columns over A. The columns of DF2 would also be the "other" columns. </p>
  
  <p>For example for </p>
  
  <pre><code>DF1 = sql_sc.createDataFrame([(1, 2,3), (2, 4,6), (3, 6,9), (4, 8,12), (5, 10,15)], ["A", "B","C"])    
  </code></pre>
  
  <p>The result would be a table as:</p>
  
  <pre><code> DF2 = sql_sc.createDataFrame([(2,3), (2,3), (2,3), (2,3), (2,3)], ["B","C"]
  </code></pre>
  
  <p>How can I do this task in pyspark SQL ?</p>
  
  <p>Thanks</p>