![]() ![]() ![]() (They're actually RETAINED, so if you overwrite them with changes, they will not reset on new records from the longer dataset). However, with BY values that yield duplicates on BOTH sides, you get what you have there: a side-by-side merge, and if one runs out before the other, the values from the last row of the shorter dataset (for that by value) are more-or-less copied down. With BY values that yield unique records per value on either side (or both), it is effectively identical to SQL. Take the next record from the right side dataset, if one exists with that BY valueĬontinue until both datasets are exhausted for that BY value Take the next record from the left side dataset, if one exists with that BY value MERGE is used to name the input data sets. It is done in a data step with the statements. SAS Merging creates a new data set (the merged dataset). Thus, it cannot create a Cartesian product in its normal process - that would require random access, which the SAS datastep doesn't do normally. SAS Merging combines observations from two or more SAS datasets based on the values of specified common variables (SAS merges more than 2 Datasets). It still processes rows iteratively, one at a time - it never goes back, and never has more than one row from any dataset in the PDV at once. MERGE is really nothing more than a special case of SET. SAS data step, however, process merges very differently. This is a Cartesian Product (at the key level). SQL creates a separate record for each possible combination of keys. Which I guess, (like an Inner Join) is not always the case.īasically, this is a result of the difference in how the SAS data step and SQL process their respective join/merges. Only include rows that match on the by variables from both input data ThisRecordIsFromYourData and ThisRecordIsFromOtherData will make SAS I want to know the concept and STEP BY STEP working of merge statement in SAS with In= and proving the above result.Īn obvious use for these variables is to control what kind of 'merge' Result: (As expected from an inner join) a 1 10 x Select data1.id,sn,sales,x from data2 inner join data1 on data1.hh_id Result: (I was expecting an Inner Join result which is not the case) 1 a 10 x I am merging them from below code: data join But if there are some 1's, then it is the first value=1 date.I have two dataset data1 and data2 data data1 If there are no 1's, then the _cutoff_date is the first value=0 date. If first.category then _cutoff_date=date Set have (where=(value=1) in=firstpass) have (in=secondpass) If you want to keep them all, then the following program will do: The WHERE data set option and statement filters unwanted rows of data. If it is in the other table then move/copy as is appropriate. I have assumed that someothercolumn is already in mergeinputtable1. ![]() If you want to delete them all, then above program works. 1 Neither If you must use a Data step then your WHERE data set option should be used earlier rather than later. what do you want to do if a given sub/category has only zeroes? You haven't answer question (or my comment above). In such a case, the program above will drop all obs for that sub/category. The hash OUTPUT method will overwrite a SAS data set, but not append. What you haven't explained is what you want to do if a given sub/category has no observations with value^=0. ![]() So assume data sorted by sub/category/date. This assumes that data are already sorted by sub/category (and presumably you require the data to be sorted by date within each sub/category). If first.category=1 then _n_of_ones=value You apparently want to delete "leading zeroes" for each sub/category combination. ![]()
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