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Of course, before you can merge the data sets, you mustsort them by IdNumber. When the data sets aremerged, SAS takes care of adding the players' names to the data set. However,it is more efficient to make use of the data set FINANCE, which already containsthe name and employee ID number of all players (see The COMPANY and FINANCE Data Sets). Of course, it is possible to re-create the data set, enteringeach player's name instead of the employee ID number in the raw data. However, casting decisionsare now final, and the manager wants to replace each employee ID number withthe player's name. To maintain confidentiality during preliminary casting,this data set identifies players by employee ID number. The following output displays the REPERTORY data set: The following program creates and displays REPERTORY: Is the employee ID number of theplayer playing Role. Is the name of one of the plays inthe repertory. The Little Theaterhas a third data set, REPERTORY, that tracks the casting assignments in eachof the season's plays. Match-Merging Data Sets with Multiple Observations in a BY Group In this case, the values ofthe variables that are unique to FINANCE (IdNumber and Salary) are missing. The data set FINANCE doesnot have an observation for Michael Morrison. Notice in particular the fourth observation. Each observation contains all the variables from both datasets. The new data set contains one observation for each playerin the company. The following output displays the merged data set: Explanation The following program merges them by NAME: The data sets are already sorted by NAME, so no furthersorting is required. Therefore, Name is the appropriate BY variable. The variable that iscommon to both data sets is Name. To avoid having to maintain two separate data sets,the director wants to merge the records for each player from both data setsinto a new data set that contains all the variables. Notice that the FINANCEdata set does not contain an observation for Michael Morrison. The following output displays the data sets. The following program creates,sorts, and displays COMPANYand FINANCE: Indiscussions of match-merging, BY groups commonly span more than one data set.įor example, the director of a small repertory theatercompany, the Little Theater, maintains company records in two SAS data sets,COMPANY and FINANCE. Ifyou use more than one variable in a BY statement, then a BY group is the setof observations with a unique combination of values for those variables. Is the set of all observations withthe same value for the BY variable (if there is only one BY variable). In order to understand match-merging, you must understandthree key concepts: BY variable

Before you can perform a match-merge, all data sets must be sortedby the variables that you want to use for the merge. Merging with a BY statement enables youto match observations according to the values of the BY variables that youspecify. Merging SAS Data Sets One to Many To match-merge data sets that have one-to-many or many-to-one relationships, you use a DATA step with the MERGE. When you match-merge data sets that have a one-to-one relationship, the output data set has the same number of observations as the input data sets. However, on subsequent iterations of the MERGE statement for. It is correct that in a one-to-one merge, and for the first matching observation in a one-to-many merge, the value of a common variable in the latter data set (s) overwrites the value from the previous data set. Proc sql Create view PapersAndTheirAuthors as select. Our usual Base SAS® approach is to join the tables with Proc sql – creating either a data file or a view. SQL JOIN We want to join (merge) three tables on two different keys. Three methods we will look at include the SQL join, the common sort-and-merge technique, and a one Data step method. Educational data about students appear in multiple files, one per class (e.g. But what about the case where there is not a unique record in both cases, known as a many-to-many merge? The SAS system joins the observations depends on whether a BY statement accompanies the MERGE statement” 1 Why does SAS offer this tool? Here are some “every day” examples of why you might want to combine data. There is at least one dataset with a sequence of variables that create a unique record identifier. Most merges are 1-to-1 or 1-to-many, i.e. As a SAS® Programmer, one of our common tasks is to merge data from two or more datasets.