![]() ![]() If the subsetting if statement is true SAS will continue processing the rest of the data step, including the implicit output. The value will be one for a row that is read from the mfg table. It will take on a value of either zero or one. This inMfg variable will be included in the PDV during execution. So after the mfg table, we will add IN=, and we’ll create a variable called inMfg. We can use the IN= data set option to control which rows are output. Remember, we would only like to include in our output table the 4 manufacturers and models that were in the cars table in our output table. For example, in the Venn diagram below, the coloured regions (Car Manufacturer and Car Mileage) represent a Left merge. Left MergeĪ Left Merge provides matched observations from two or more datasets while retaining all mismatched observations from the first (left) data set. So, we’ll sort the data by both mfg and model. In other words, we want to eliminate the non-matches. So we will need to limit the rows in our output table to only those that match. In the previous example we saw, we have a total of 6 rows. ![]() So we would like to merge these two tables to include the mileage column with the mfg table. However, that information is contained in the cars table. In the Mfg table, we have information about the Car Manufacturer, Model, and price. We’ll use the data step merge to combine two tables and identify non-matching rows. So how can you use these IN= variables in your program to subset the output table?įor example, how could you include only the matching rows in your output table? You probably already know the answer, so let’s see if you get it right. Zero means that the table does not include the by column value for that row, and one means it does have the by column value.įor example, honda is only in the mfg table, so inCars is zero and inMfg is one.Īnd the opposite is true for isuz. PDV during the merge processĭuring execution, the in= variables are assigned a value of zero or one. Each IN= variable is associated with a particular table that the option follows. The IN= variables are included in the PDV during execution but are not written to the output table. The IN= dataset option follows one or more tables on the merge statement and names a temporary variable that is added to the PDV. You can use the IN= dataset option to create temporary variables in the PDV that you can use to flag matching or non-matching values. Or suppose you want to identify missing cars in one of the tables. For example, suppose you only want to include cars that are on both tables. The output dataset you create when you merge tables with non-matching rows might not be what you want. The rows for Honda and isuz have missing values for the columns in the tables where they were not included. What happens to those non-matching rows in the data step merge? data Mergedata Īlthough both input tables have 4 rows, the output table Mergedata has 6 rows because it includes both Honda and isuz. ![]()
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