title: Read csv in Spark with skip rows
body: <p>I am trying to load data from a csv file to a DataFrame. I must use the <code>spark.read.csv()</code> function, because <code>rdd sc.fileText()</code> does not work with the specific data in file (there are invisible comma characters in the csv data, <code>rdd sc.fileText()</code> splits them). The csv file has a few rows to skip on the start:</p>
  
  <pre><code>Report &lt;- to skip
  Generated by YYYY-MM-DD &lt;- to skip
  Sessions &lt;- to skip
  &lt;- to skip
  Session of all hosts &lt;- to skip
  col1,col2,col3,col4,col5 &lt;- it is my header
  tst1,tst2,tst3,tst4,tst5 &lt;- my data start here
  tst6,tst7,tst8,tst9,tst10
  ...
  </code></pre>
  
  <p>I want to have a dataframe like this:</p>
  
  <pre><code>tst1,tst2,tst3,tst4,tst5 &lt;- data
  tst6,tst7,tst8,tst9,tst10
  </code></pre>
  
  <p>I tried to use the map and filter functions, but it does not work properly:</p>
  
  <pre><code>.rdd.map(lambda line: str(line).split(','))\
  .filter(lambda line: len(line)&gt;3).collect()
  </code></pre>