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Data Integration (“Unions” (to access more observations) (are performed…

- - - - produces the same result as an inner join, but also adds any rows from the right table that do not have corresponding rows in the left table
    - - produces the same result as an inner join + a left outer join + a right outer join
    - - produces the same result as an inner join but also adds any rows from the left table that do not have corresponding rows in the right table
      - most useful when engaged in a project with the goal being to collect as much customer data as possible
      - inner join together will take care of 99% of related needs
- - - - generally undesirable to develop separate processes for the training and test data (it increases the likelihood of producing a mistake in one of the processes but not the other)
    - - assign the average (ex: average age) to every column in which the value is missing
        
        Calculating the average for both datasets is often better than doing so for just one of them as it is more representative of the total population (to generalize, more data points produces a more accurate average)