anchor.diff:  <1> We're interested in knowing the summary statistics about the Fare column.
   <2> We want Spark to show us the results.
   
  -The query should return a Dataset containing the information in table 2.4.
  +The query should return a Dataset containing the information in table 2.6.
   
   .Results of calling the describe method on the Fare column.
   [options="header"]
  
positive.code: 
  In the same way we had rows without Age in the training dataset, we have some
  also in the test dataset. However, in this dataset, we have one row without
  Fare, which you can see with the code in listing 2.16.
  
  .Obtaining the row without Fare in the test DataFrame.
  [source,scala]
  
negative.code: the label column (Survived) contains integers as indicated by the
  `printSchema()` method we used at the beginning of the chapter (listing 2.2).
  To remedy this, we're going to cast our Survived column to double in listing
  2.14.
  
  .Casting the Survived column to double.
  [source,scala]
  