anchor.diff:  {transform}. 
   +
   --
  -.. Supply a job ID and the name of the target (or _destination_) index.
  +.. Supply a job ID and the name of the target (or _destination_) index. If the
  +target index does not exist, it will be created automatically.
   
   .. Decide whether you want the {transform} to run once or continuously.
   --
  
positive.code: . Play with various options for grouping and aggregating the data. 
  +
  --
  For example, you might want to group the data by product ID and calculate the
  total number of sales for each product and its average price. Alternatively, you
  might want to look at the behavior of individual customers and calculate how
  
negative.code: consideration. What are the most interesting ways you can transform and
  interpret this data?
  
  Go to *Machine Learning* > *Data Frames* in {kib} and use the
  wizard to create a {transform}:
  
  [role="screenshot"]
  