![]() ![]() ![]() It can also be used as a powerful look up tool where blocks of observations require combining or looking up information in a corresponding single observation in another data set. SAS Techies 2009 LINK Statement data hydro input type $ depth station $ if type ='aluv' then link calcu date=today() return calcu: if station='site_1' then elevatn=6650-depth else if station='site_2' then elevatn=5500-depth return datalines aluv 523 site_1 uppa 234 site_2 aluv 666 site_2. INTRODUCTION The data step language with the MERGE and BY statements provides a powerful method for doing one-to-one combining of data.SAS Techies 2009 Proc sort data=a by num Proc sort data=b by num data sharad merge a b by num run data sharad set a b run 11/13/09.SAS Techies 2009 data lab23.drug1h set research.cltrials if placebo='YES' run data lab23.drug1h set research.cltrials Where placebo='YES' run data lab23.drug1h set research.cltrials ( Where=( placebo='YES‘)) run data lab23.drug1h set A C run 11/13/09.The BY variable(s) must be present in all data sets, and the names of the key. The more useful and therefore much more common merge performed in SAS is what is called match-merging. Data sets must be sorted by or indexed on the BY variable(s) prior to merging. It's for this reason that I personally don't find the one-to-one read or the one-to-one merge all that practical. It would just take one of the data sets to be "shifted" ever so slightly to get really messed up results. One-to-one reading and one-to-one merging require users to exercise extreme caution when combining two (or more) data sets based on relative position only. The optional arguments are the data set options. You can keep adding more arguments to join more tables. Now, launch and run the SAS program, and review the output to convince yourself that the one and two data sets are combined as described. MERGE SAS-data-set-1 < ( data-set-options )> SAS-data-set-2 < ( data-set-options) > < SAS-data-set-n < ( data-set-options )> The MERGE statement contains at least two obligatory arguments, namely the SAS tables you want to join.Because there are no more observations in either the one or the two data set, processing stops. Let's go back to our contrived example to illustrate this point.īeing at the end of the third iteration of the DATA step, SAS writes the contents of the program data vector as the third observation in the onetwomerged SAS data set. Just as is true for one-to-one reading, if data sets that are being one-to-one merged contain variables that have the same names, the values that are read in from the last data set overwrite the values that were read in from earlier data sets. Note that although this example only combined two data sets, the MERGE statement can contain any number of input data sets. Since there are seven observations in patients and six observations in scale, the new one2onemerge data set contains seven observations, with missing values for the Height and Weight variables in the seventh observation. You should see that the first observation in one2onemerge contains the first observation of patients and scale, the second observation in one2onemerge contains the second observation of patients and scale, and so on. Launch and run the SAS program and review the output from the PRINT procedure to see the results of the one-to-one merge. The MERGE statement tells SAS to create a new data set by combining patients and scale. ![]()
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