Choose Remove to remove a variable from the Sort list box. Multiple variables can be selected and removed at one time and the variables selected can be contiguous or non-contiguous. Multiple variables contiguous and non-contiguous can be selected and moved at one time using these options. Choose Merge to create the output file and display the output record count. Selecting the Close button will close the Merge dialog box.
Related topics:. Join two files together. We would like to match merge the files together so we have the dads observation on the same line with the faminc observation based on the key variable famid.
Below we create the files dads. There are three steps to match merge dads. Note that this is a one to one merge because there is a one to one correspondence between the dads and faminc records. These three steps are illustrated below.
The next example considers a one to many merge where one observation in one file may have multiple matching records in another file. Imagine that we had a file with dads like we saw in the previous example, and we had a file with kids where a dad could have more than one kid.
You see why this is called a one to many merge since you are matching one dad observation to one or more many kids observations. Remember that the dads file is the file with one observation, and the kids file is the one with many observations.
Below, we create the data file for the dads and for the kids. As you see below, the steps for doing a one to many merge is similar to the one to one merge that we saw above. For your data, when you do a one to many merge, ask yourself which file plays the role of one in one to many. The first thing we notice is that SPSS gives us the warning shown below.
This is telling us that there are multiple kids for a given dad. As SPSS advises, we will inspect the results carefully. I refer to two files as having an identical structure if they contain the "same" variables. This means that 1 all variables that are in one file are also present in the other file s and that no file contains variables that are not present in other files, and that 2 all the variables in all files that have the same name are of the same type.
If the first condition is violated — i. The second case will be detrimental, that is, the operation of ADDing files will not be performed. I will deal with these two cases in turn. Let's assume you have two data sets you wish to ADD. Data set 'data1.
What happens if you ADD the two files? The resulting data set will have variables var1, var2 and var3, and the cases from 'data1. Of course this may be precisely what you want, but if you do not need var3, it may be good practice to drop it from the resulting data set, because each 'useless' variable makes itself felt negatively as far as computational speed is concerned.
This can be achieved easily like this:. Note that of course you may always use the "drop" or "keep" commands to get rid of variables you do not need. A problem that may occur if you have not prepared your data well, that is is that you have the same variables in both data sets, but these are named differently.
Let's assume that 'data1. But unfortunately, in 'data1. For instance, 'data1. Instead, what is called var2 contains data that you do not need anymore. Thus, you will write:. You have to change the type of the variable prior to ADDing files.
The interesting thing is which variables will be treated as 'of the same type' and which will not. I deal here only with the most usual cases, that is numeric and string variables. When you are done, you can restore the full set of data. When you are done with doing an analysis on your filtered subset, you can restore the full set of data using the following syntax. Merging two datasets by id, which is a unique case identifier.
If you are adding variables, click Data -merge file -add variables. From the menus choose: Data Merge Files. Each case has a unique id identifier in each data source.
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