![]() ![]() That is why for ID=5, the value is missing in MergeWant. While Want contains only 1.įurthermore, the Update Statement does not overwrite observations with missing values by default. Consequently, MergeWant contains 3 observations for ID=4. However, with the Merge Statement, SAS outputs as many observations for each By-Group as the number of observations in the By-Group with the highest number of observations. With an Update, SAS does not write an updated observation to the new data set until it has applied all the transactions in a BY group. This is due to the way that the two statements process multiple observations in the same By-Group. And how they deal with missing values.Īs you have seen, the MergeWant data set contains two observations more than the Wand data set. ![]() Namely how they process multiple observations in by groups. That is not the case with the Merge Statement.īesides the two differences above, there are two fundamental differences in the way the the two statements processes data. Also, a By Statement must follow the Update Statement immediately. On the other hand, the Merge can handle as much as 256 data sets. As a consequence, SAS appends a new observation to the output data set.ĭata MergeWant merge Master Trans by ID run įirst and foremost, the Update Statement deals with exactly two data sets. However, it does not in the Master data set. Even though an observation exists for ID=5 in the Transaction data set, SAS does not overwrite because it is a missing value.įinally, notice that an observation for ID=6 exists in the Transaction data set. For ID=5, Value=5 in the Master data set. You can change this behavior with Updatemode=Nomissingcheck. This means that missing values in the Transaction data set do not overwrite values in the Master data set. In the code below, I specify Updatemode=Missingcheck. Notice that for ID=2, SAS only updates the first observation.Īn important feature of the Update Statement is how it deals with missing values. Consequently, SAS updates only the first observation for each By-Group. If multiple observations exist for the same ID in the Master data set, SAS ignores these. That means, that if multiple observations exists for the same ID in the transaction data set, only the last observation will be updated to the output data set in the end. Next, SAS applies all the transactions for the relevant ID to the observation. SAS reads in the first observation from the Update Statement into the PDV. This is a requirement for the input data sets in the Update Statement. In the code below, I create A Master and a Transaction data set to demonstrate. The Update Statement is best explained by an example. The SAS Update Statement updates a Master data set with Transactions from a Transaction data set. This post demonstrates how to use the Update Statement by example. However, it can be a quite handy tool under the right circumstances. ![]() Most SAS programmers know about the Set Statement and the Merge Statement in the Data Step. ![]()
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